Comments (3)
wangxinyu0922
commented on June 19, 2024
This bug only occurs when the length of tokenized sentence exceeds the maximum subtoken length of the transformer embeddings. For example, this sentence in your dev set exceeds the limit of 512 subtokens.
I fixed this problem in the newest version of the code (embeddings.py), so you may not worry about the subtoken length in the newest version.
from ace.
jcazeredo
commented on June 19, 2024
Thank you for your fast answer. Unfortunately, I only had time to test it today. It seems another error it's showing up.
/content/tcc# bash run_train.sh /content/tcc/ace_config_files/xlnet-base-doc.yaml
2021-10-25 22:56:02,380 Reading data from /content/tcc/data/harem_conll
2021-10-25 22:56:02,380 Train: /content/tcc/data/harem_conll/harem_default.train
2021-10-25 22:56:02,380 Dev: /content/tcc/data/harem_conll/harem_default.dev
2021-10-25 22:56:02,380 Test: /content/tcc/data/harem_conll/harem_default.test
2021-10-25 22:56:06,701 {b'<unk>': 0, b'<START>': 1, b'<STOP>': 2, b'O': 3, b'B-PESSOA': 4, b'I-PESSOA': 5, b'S-PESSOA': 6, b'E-PESSOA': 7, b'B-ORGANIZACAO': 8, b'I-ORGANIZACAO': 9, b'S-ORGANIZACAO': 10, b'E-ORGANIZACAO': 11, b'B-TEMPO': 12, b'I-TEMPO': 13, b'S-TEMPO': 14, b'E-TEMPO': 15, b'B-LOCAL': 16, b'I-LOCAL': 17, b'S-LOCAL': 18, b'E-LOCAL': 19, b'B-OBRA': 20, b'I-OBRA': 21, b'S-OBRA': 22, b'E-OBRA': 23, b'B-ACONTECIMENTO': 24, b'I-ACONTECIMENTO': 25, b'S-ACONTECIMENTO': 26, b'E-ACONTECIMENTO': 27, b'B-ABSTRACCAO': 28, b'I-ABSTRACCAO': 29, b'S-ABSTRACCAO': 30, b'E-ABSTRACCAO': 31, b'B-COISA': 32, b'I-COISA': 33, b'S-COISA': 34, b'E-COISA': 35, b'B-VALOR': 36, b'I-VALOR': 37, b'S-VALOR': 38, b'E-VALOR': 39, b'B-VARIADO': 40, b'I-VARIADO': 41, b'S-VARIADO': 42, b'E-VARIADO': 43}
2021-10-25 22:56:06,701 Corpus: 5155 train + 138 dev + 3658 test sentences
[2021-10-25 22:56:07,469 DEBUG] Attempting to acquire lock 140682438270672 on /root/.cache/torch/transformers/c9cc6e53904f7f3679a31ec4af244f4419e25ebc8e71ebf8c558a31cbcf07fc8.69e5e35e0b798cab5e473f253752f8bf4d280ee37682281a23eed80f6e2d09c6.lock
[2021-10-25 22:56:07,470 DEBUG] Lock 140682438270672 acquired on /root/.cache/torch/transformers/c9cc6e53904f7f3679a31ec4af244f4419e25ebc8e71ebf8c558a31cbcf07fc8.69e5e35e0b798cab5e473f253752f8bf4d280ee37682281a23eed80f6e2d09c6.lock
[2021-10-25 22:56:07,470 INFO] https://s3.amazonaws.com/models.huggingface.co/bert/xlnet-base-cased-config.json not found in cache or force_download set to True, downloading to /root/.cache/torch/transformers/tmpuusfad4i
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[2021-10-25 22:56:08,235 INFO] storing https://s3.amazonaws.com/models.huggingface.co/bert/xlnet-base-cased-config.json in cache at /root/.cache/torch/transformers/c9cc6e53904f7f3679a31ec4af244f4419e25ebc8e71ebf8c558a31cbcf07fc8.69e5e35e0b798cab5e473f253752f8bf4d280ee37682281a23eed80f6e2d09c6
[2021-10-25 22:56:08,235 INFO] creating metadata file for /root/.cache/torch/transformers/c9cc6e53904f7f3679a31ec4af244f4419e25ebc8e71ebf8c558a31cbcf07fc8.69e5e35e0b798cab5e473f253752f8bf4d280ee37682281a23eed80f6e2d09c6
[2021-10-25 22:56:08,236 DEBUG] Attempting to release lock 140682438270672 on /root/.cache/torch/transformers/c9cc6e53904f7f3679a31ec4af244f4419e25ebc8e71ebf8c558a31cbcf07fc8.69e5e35e0b798cab5e473f253752f8bf4d280ee37682281a23eed80f6e2d09c6.lock
[2021-10-25 22:56:08,236 DEBUG] Lock 140682438270672 released on /root/.cache/torch/transformers/c9cc6e53904f7f3679a31ec4af244f4419e25ebc8e71ebf8c558a31cbcf07fc8.69e5e35e0b798cab5e473f253752f8bf4d280ee37682281a23eed80f6e2d09c6.lock
[2021-10-25 22:56:08,236 INFO] loading configuration file https://s3.amazonaws.com/models.huggingface.co/bert/xlnet-base-cased-config.json from cache at /root/.cache/torch/transformers/c9cc6e53904f7f3679a31ec4af244f4419e25ebc8e71ebf8c558a31cbcf07fc8.69e5e35e0b798cab5e473f253752f8bf4d280ee37682281a23eed80f6e2d09c6
[2021-10-25 22:56:08,237 INFO] Model config XLNetConfig {
"architectures": [
"XLNetLMHeadModel"
],
"attn_type": "bi",
"bi_data": false,
"bos_token_id": 1,
"clamp_len": -1,
"d_head": 64,
"d_inner": 3072,
"d_model": 768,
"dropout": 0.1,
"end_n_top": 5,
"eos_token_id": 2,
"ff_activation": "gelu",
"initializer_range": 0.02,
"layer_norm_eps": 1e-12,
"mem_len": null,
"model_type": "xlnet",
"n_head": 12,
"n_layer": 12,
"pad_token_id": 5,
"reuse_len": null,
"same_length": false,
"start_n_top": 5,
"summary_activation": "tanh",
"summary_last_dropout": 0.1,
"summary_type": "last",
"summary_use_proj": true,
"task_specific_params": {
"text-generation": {
"do_sample": true,
"max_length": 250
}
},
"untie_r": true,
"vocab_size": 32000
}
[2021-10-25 22:56:08,993 DEBUG] Attempting to acquire lock 140682432921936 on /root/.cache/torch/transformers/dad589d582573df0293448af5109cb6981ca77239ed314e15ca63b7b8a318ddd.8b10bd978b5d01c21303cc761fc9ecd464419b3bf921864a355ba807cfbfafa8.lock
[2021-10-25 22:56:08,994 DEBUG] Lock 140682432921936 acquired on /root/.cache/torch/transformers/dad589d582573df0293448af5109cb6981ca77239ed314e15ca63b7b8a318ddd.8b10bd978b5d01c21303cc761fc9ecd464419b3bf921864a355ba807cfbfafa8.lock
[2021-10-25 22:56:08,994 INFO] https://s3.amazonaws.com/models.huggingface.co/bert/xlnet-base-cased-spiece.model not found in cache or force_download set to True, downloading to /root/.cache/torch/transformers/tmpjsbq5tgb
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[2021-10-25 22:56:10,876 INFO] storing https://s3.amazonaws.com/models.huggingface.co/bert/xlnet-base-cased-spiece.model in cache at /root/.cache/torch/transformers/dad589d582573df0293448af5109cb6981ca77239ed314e15ca63b7b8a318ddd.8b10bd978b5d01c21303cc761fc9ecd464419b3bf921864a355ba807cfbfafa8
[2021-10-25 22:56:10,876 INFO] creating metadata file for /root/.cache/torch/transformers/dad589d582573df0293448af5109cb6981ca77239ed314e15ca63b7b8a318ddd.8b10bd978b5d01c21303cc761fc9ecd464419b3bf921864a355ba807cfbfafa8
[2021-10-25 22:56:10,876 DEBUG] Attempting to release lock 140682432921936 on /root/.cache/torch/transformers/dad589d582573df0293448af5109cb6981ca77239ed314e15ca63b7b8a318ddd.8b10bd978b5d01c21303cc761fc9ecd464419b3bf921864a355ba807cfbfafa8.lock
[2021-10-25 22:56:10,877 DEBUG] Lock 140682432921936 released on /root/.cache/torch/transformers/dad589d582573df0293448af5109cb6981ca77239ed314e15ca63b7b8a318ddd.8b10bd978b5d01c21303cc761fc9ecd464419b3bf921864a355ba807cfbfafa8.lock
[2021-10-25 22:56:10,877 INFO] loading file https://s3.amazonaws.com/models.huggingface.co/bert/xlnet-base-cased-spiece.model from cache at /root/.cache/torch/transformers/dad589d582573df0293448af5109cb6981ca77239ed314e15ca63b7b8a318ddd.8b10bd978b5d01c21303cc761fc9ecd464419b3bf921864a355ba807cfbfafa8
[2021-10-25 22:56:11,676 INFO] loading configuration file https://s3.amazonaws.com/models.huggingface.co/bert/xlnet-base-cased-config.json from cache at /root/.cache/torch/transformers/c9cc6e53904f7f3679a31ec4af244f4419e25ebc8e71ebf8c558a31cbcf07fc8.69e5e35e0b798cab5e473f253752f8bf4d280ee37682281a23eed80f6e2d09c6
[2021-10-25 22:56:11,677 INFO] Model config XLNetConfig {
"architectures": [
"XLNetLMHeadModel"
],
"attn_type": "bi",
"bi_data": false,
"bos_token_id": 1,
"clamp_len": -1,
"d_head": 64,
"d_inner": 3072,
"d_model": 768,
"dropout": 0.1,
"end_n_top": 5,
"eos_token_id": 2,
"ff_activation": "gelu",
"initializer_range": 0.02,
"layer_norm_eps": 1e-12,
"mem_len": null,
"model_type": "xlnet",
"n_head": 12,
"n_layer": 12,
"output_hidden_states": true,
"pad_token_id": 5,
"reuse_len": null,
"same_length": false,
"start_n_top": 5,
"summary_activation": "tanh",
"summary_last_dropout": 0.1,
"summary_type": "last",
"summary_use_proj": true,
"task_specific_params": {
"text-generation": {
"do_sample": true,
"max_length": 250
}
},
"untie_r": true,
"vocab_size": 32000
}
[2021-10-25 22:56:11,780 DEBUG] Attempting to acquire lock 140682086723536 on /root/.cache/torch/transformers/33d6135fea0154c088449506a4c5f9553cb59b6fd040138417a7033af64bb8f9.7eac4fe898a021204e63c88c00ea68c60443c57f94b4bc3c02adbde6465745ac.lock
[2021-10-25 22:56:11,780 DEBUG] Lock 140682086723536 acquired on /root/.cache/torch/transformers/33d6135fea0154c088449506a4c5f9553cb59b6fd040138417a7033af64bb8f9.7eac4fe898a021204e63c88c00ea68c60443c57f94b4bc3c02adbde6465745ac.lock
[2021-10-25 22:56:11,780 INFO] https://cdn.huggingface.co/xlnet-base-cased-pytorch_model.bin not found in cache or force_download set to True, downloading to /root/.cache/torch/transformers/tmpntn_k5u7
Downloading: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 467M/467M [00:11<00:00, 39.8MB/s]
[2021-10-25 22:56:23,569 INFO] storing https://cdn.huggingface.co/xlnet-base-cased-pytorch_model.bin in cache at /root/.cache/torch/transformers/33d6135fea0154c088449506a4c5f9553cb59b6fd040138417a7033af64bb8f9.7eac4fe898a021204e63c88c00ea68c60443c57f94b4bc3c02adbde6465745ac
[2021-10-25 22:56:23,570 INFO] creating metadata file for /root/.cache/torch/transformers/33d6135fea0154c088449506a4c5f9553cb59b6fd040138417a7033af64bb8f9.7eac4fe898a021204e63c88c00ea68c60443c57f94b4bc3c02adbde6465745ac
[2021-10-25 22:56:23,570 DEBUG] Attempting to release lock 140682086723536 on /root/.cache/torch/transformers/33d6135fea0154c088449506a4c5f9553cb59b6fd040138417a7033af64bb8f9.7eac4fe898a021204e63c88c00ea68c60443c57f94b4bc3c02adbde6465745ac.lock
[2021-10-25 22:56:23,570 DEBUG] Lock 140682086723536 released on /root/.cache/torch/transformers/33d6135fea0154c088449506a4c5f9553cb59b6fd040138417a7033af64bb8f9.7eac4fe898a021204e63c88c00ea68c60443c57f94b4bc3c02adbde6465745ac.lock
[2021-10-25 22:56:23,570 INFO] loading weights file https://cdn.huggingface.co/xlnet-base-cased-pytorch_model.bin from cache at /root/.cache/torch/transformers/33d6135fea0154c088449506a4c5f9553cb59b6fd040138417a7033af64bb8f9.7eac4fe898a021204e63c88c00ea68c60443c57f94b4bc3c02adbde6465745ac
[2021-10-25 22:56:25,831 INFO] All model checkpoint weights were used when initializing XLNetModel.
[2021-10-25 22:56:25,832 INFO] All the weights of XLNetModel were initialized from the model checkpoint at xlnet-base-cased.
If your task is similar to the task the model of the ckeckpoint was trained on, you can already use XLNetModel for predictions without further training.
2021-10-25 22:56:38,416 Model Size: 116752172
Corpus: 5034 train + 130 dev + 3530 test sentences
2021-10-25 22:56:38,448 ----------------------------------------------------------------------------------------------------
2021-10-25 22:56:38,449 Model: "FastSequenceTagger(
(embeddings): StackedEmbeddings(
(list_embedding_0): TransformerWordEmbeddings(
(model): XLNetModel(
(word_embedding): Embedding(32000, 768)
(layer): ModuleList(
(0): XLNetLayer(
(rel_attn): XLNetRelativeAttention(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(ff): XLNetFeedForward(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(layer_1): Linear(in_features=768, out_features=3072, bias=True)
(layer_2): Linear(in_features=3072, out_features=768, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(dropout): Dropout(p=0.1, inplace=False)
)
(1): XLNetLayer(
(rel_attn): XLNetRelativeAttention(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(ff): XLNetFeedForward(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(layer_1): Linear(in_features=768, out_features=3072, bias=True)
(layer_2): Linear(in_features=3072, out_features=768, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(dropout): Dropout(p=0.1, inplace=False)
)
(2): XLNetLayer(
(rel_attn): XLNetRelativeAttention(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(ff): XLNetFeedForward(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(layer_1): Linear(in_features=768, out_features=3072, bias=True)
(layer_2): Linear(in_features=3072, out_features=768, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(dropout): Dropout(p=0.1, inplace=False)
)
(3): XLNetLayer(
(rel_attn): XLNetRelativeAttention(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(ff): XLNetFeedForward(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(layer_1): Linear(in_features=768, out_features=3072, bias=True)
(layer_2): Linear(in_features=3072, out_features=768, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(dropout): Dropout(p=0.1, inplace=False)
)
(4): XLNetLayer(
(rel_attn): XLNetRelativeAttention(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(ff): XLNetFeedForward(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(layer_1): Linear(in_features=768, out_features=3072, bias=True)
(layer_2): Linear(in_features=3072, out_features=768, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(dropout): Dropout(p=0.1, inplace=False)
)
(5): XLNetLayer(
(rel_attn): XLNetRelativeAttention(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(ff): XLNetFeedForward(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(layer_1): Linear(in_features=768, out_features=3072, bias=True)
(layer_2): Linear(in_features=3072, out_features=768, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(dropout): Dropout(p=0.1, inplace=False)
)
(6): XLNetLayer(
(rel_attn): XLNetRelativeAttention(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(ff): XLNetFeedForward(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(layer_1): Linear(in_features=768, out_features=3072, bias=True)
(layer_2): Linear(in_features=3072, out_features=768, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(dropout): Dropout(p=0.1, inplace=False)
)
(7): XLNetLayer(
(rel_attn): XLNetRelativeAttention(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(ff): XLNetFeedForward(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(layer_1): Linear(in_features=768, out_features=3072, bias=True)
(layer_2): Linear(in_features=3072, out_features=768, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(dropout): Dropout(p=0.1, inplace=False)
)
(8): XLNetLayer(
(rel_attn): XLNetRelativeAttention(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(ff): XLNetFeedForward(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(layer_1): Linear(in_features=768, out_features=3072, bias=True)
(layer_2): Linear(in_features=3072, out_features=768, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(dropout): Dropout(p=0.1, inplace=False)
)
(9): XLNetLayer(
(rel_attn): XLNetRelativeAttention(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(ff): XLNetFeedForward(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(layer_1): Linear(in_features=768, out_features=3072, bias=True)
(layer_2): Linear(in_features=3072, out_features=768, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(dropout): Dropout(p=0.1, inplace=False)
)
(10): XLNetLayer(
(rel_attn): XLNetRelativeAttention(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(ff): XLNetFeedForward(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(layer_1): Linear(in_features=768, out_features=3072, bias=True)
(layer_2): Linear(in_features=3072, out_features=768, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(dropout): Dropout(p=0.1, inplace=False)
)
(11): XLNetLayer(
(rel_attn): XLNetRelativeAttention(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(ff): XLNetFeedForward(
(layer_norm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)
(layer_1): Linear(in_features=768, out_features=3072, bias=True)
(layer_2): Linear(in_features=3072, out_features=768, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
)
(dropout): Dropout(p=0.1, inplace=False)
)
)
(dropout): Dropout(p=0.1, inplace=False)
)
)
)
(word_dropout): WordDropout(p=0.1)
(linear): Linear(in_features=768, out_features=44, bias=True)
)"
2021-10-25 22:56:38,450 ----------------------------------------------------------------------------------------------------
2021-10-25 22:56:38,450 Corpus: "Corpus: 5034 train + 130 dev + 3530 test sentences"
2021-10-25 22:56:38,450 ----------------------------------------------------------------------------------------------------
2021-10-25 22:56:38,450 Parameters:
2021-10-25 22:56:38,450 - Optimizer: "AdamW"
2021-10-25 22:56:38,450 - learning_rate: "5e-06"
2021-10-25 22:56:38,450 - mini_batch_size: "1"
2021-10-25 22:56:38,451 - patience: "10"
2021-10-25 22:56:38,451 - anneal_factor: "0.5"
2021-10-25 22:56:38,451 - max_epochs: "10"
2021-10-25 22:56:38,451 - shuffle: "True"
2021-10-25 22:56:38,451 - train_with_dev: "False"
2021-10-25 22:56:38,451 - word min_freq: "-1"
2021-10-25 22:56:38,451 ----------------------------------------------------------------------------------------------------
2021-10-25 22:56:38,452 Model training base path: "/content/tcc/ACE/resources/taggers/xlnet-base-finetuned-doc"
2021-10-25 22:56:38,452 ----------------------------------------------------------------------------------------------------
2021-10-25 22:56:38,452 Device: cuda:0
2021-10-25 22:56:38,452 ----------------------------------------------------------------------------------------------------
2021-10-25 22:56:38,452 Embeddings storage mode: none
2021-10-25 22:56:39,248 ----------------------------------------------------------------------------------------------------
2021-10-25 22:56:39,253 Current loss interpolation: 1
['xlnet-base-cased_v2doc']
2021-10-25 22:56:39,526 epoch 1 - iter 0/5034 - loss 173.06898499 - samples/sec: 3.67 - decode_sents/sec: 263.89
2021-10-25 22:57:42,339 epoch 1 - iter 503/5034 - loss 21.69958575 - samples/sec: 8.53 - decode_sents/sec: 1037234.47
2021-10-25 22:58:39,224 epoch 1 - iter 1006/5034 - loss 17.54147579 - samples/sec: 9.47 - decode_sents/sec: 1095966.19
2021-10-25 22:59:35,897 epoch 1 - iter 1509/5034 - loss 16.09543247 - samples/sec: 9.52 - decode_sents/sec: 804321.35
2021-10-25 23:00:32,237 epoch 1 - iter 2012/5034 - loss 15.40342070 - samples/sec: 9.58 - decode_sents/sec: 811124.53
2021-10-25 23:01:28,478 epoch 1 - iter 2515/5034 - loss 14.86113683 - samples/sec: 9.60 - decode_sents/sec: 876499.76
2021-10-25 23:02:24,643 epoch 1 - iter 3018/5034 - loss 14.23401209 - samples/sec: 9.60 - decode_sents/sec: 1081360.80
2021-10-25 23:03:21,115 epoch 1 - iter 3521/5034 - loss 14.03165655 - samples/sec: 9.56 - decode_sents/sec: 981728.67
2021-10-25 23:04:17,405 epoch 1 - iter 4024/5034 - loss 13.73906589 - samples/sec: 9.59 - decode_sents/sec: 936411.41
2021-10-25 23:05:13,911 epoch 1 - iter 4527/5034 - loss 13.37011227 - samples/sec: 9.54 - decode_sents/sec: 861819.82
2021-10-25 23:06:10,821 epoch 1 - iter 5030/5034 - loss 13.24819737 - samples/sec: 9.48 - decode_sents/sec: 939329.88
2021-10-25 23:06:11,204 ----------------------------------------------------------------------------------------------------
2021-10-25 23:06:11,205 EPOCH 1 done: loss 3.3130 - lr 5e-06
2021-10-25 23:06:11,205 ----------------------------------------------------------------------------------------------------
2021-10-25 23:06:16,174 Macro Average: 34.38 Macro avg loss: 16.14
ColumnCorpus-1 34.38
2021-10-25 23:06:16,177 ----------------------------------------------------------------------------------------------------
2021-10-25 23:06:16,177 BAD EPOCHS (no improvement): 11
2021-10-25 23:06:16,177 GLOBAL BAD EPOCHS (no improvement): 0
2021-10-25 23:06:16,177 ==================Saving the current best model: 34.38==================
2021-10-25 23:06:17,697 ==================Saving the best language model: 34.38==================
[2021-10-25 23:06:17,701 INFO] Configuration saved in /content/tcc/ACE/resources/taggers/xlnet-base-finetuned-doc/xlnet-base-cased_v2doc/config.json
[2021-10-25 23:06:19,510 INFO] Model weights saved in /content/tcc/ACE/resources/taggers/xlnet-base-finetuned-doc/xlnet-base-cased_v2doc/pytorch_model.bin
2021-10-25 23:06:19,511 ----------------------------------------------------------------------------------------------------
2021-10-25 23:06:19,518 Current loss interpolation: 1
['xlnet-base-cased_v2doc']
2021-10-25 23:06:19,633 epoch 2 - iter 0/5034 - loss 3.79385304 - samples/sec: 8.69 - decode_sents/sec: 913.99
2021-10-25 23:07:16,711 epoch 2 - iter 503/5034 - loss 11.27529993 - samples/sec: 9.46 - decode_sents/sec: 747073.27
2021-10-25 23:08:13,573 epoch 2 - iter 1006/5034 - loss 11.36842699 - samples/sec: 9.49 - decode_sents/sec: 724745.76
2021-10-25 23:09:10,274 epoch 2 - iter 1509/5034 - loss 10.85687287 - samples/sec: 9.52 - decode_sents/sec: 910939.08
2021-10-25 23:10:07,269 epoch 2 - iter 2012/5034 - loss 10.61978362 - samples/sec: 9.47 - decode_sents/sec: 614545.56
2021-10-25 23:11:03,874 epoch 2 - iter 2515/5034 - loss 10.74376967 - samples/sec: 9.54 - decode_sents/sec: 982185.71
2021-10-25 23:12:00,804 epoch 2 - iter 3018/5034 - loss 10.59236796 - samples/sec: 9.47 - decode_sents/sec: 882365.08
2021-10-25 23:12:57,251 epoch 2 - iter 3521/5034 - loss 10.48515464 - samples/sec: 9.56 - decode_sents/sec: 922893.66
2021-10-25 23:13:54,211 epoch 2 - iter 4024/5034 - loss 10.41603058 - samples/sec: 9.47 - decode_sents/sec: 879056.21
2021-10-25 23:14:51,117 epoch 2 - iter 4527/5034 - loss 10.35569958 - samples/sec: 9.48 - decode_sents/sec: 596475.80
2021-10-25 23:15:48,052 epoch 2 - iter 5030/5034 - loss 10.38159148 - samples/sec: 9.47 - decode_sents/sec: 894334.43
2021-10-25 23:15:48,435 ----------------------------------------------------------------------------------------------------
2021-10-25 23:15:48,435 EPOCH 2 done: loss 2.5969 - lr 4.5e-06
2021-10-25 23:15:48,436 ----------------------------------------------------------------------------------------------------
Traceback (most recent call last):
File "./ACE/train.py", line 360, in <module>
getattr(trainer,'train')(**train_config)
File "/content/tcc/ACE/flair/trainers/finetune_trainer.py", line 778, in train
embeddings_storage_mode=embeddings_storage_mode,
File "/content/tcc/ACE/flair/models/sequence_tagger_model.py", line 2270, in evaluate
del batch.features
AttributeError: features
/content/tcc#
from ace.
wangxinyu0922
commented on June 19, 2024
Oops, fixed that.
from ace.
Related Issues (20)
- Issue with running requirements.txt HOT 1
- Requirements.txt versions HOT 3
- Confuse about the SDP dataset HOT 2
- Is GPU required? HOT 4
- AttributeError: 'NoneType' object has no attribute 'tokenize' HOT 7
- Test result comparison without vs with document-level features HOT 18
- Embeddings Availability HOT 3
- Testing on my own data file HOT 1
- Using your best model for inference for NER in production HOT 4
- Missing B-ORG but with I-ORG and E-ORG HOT 2
- Test PTB Dependency Parsing Model HOT 9
- How to apply ACE model as a parser tool for DM parsing? HOT 3
- Change the directory of downloading HOT 1
- How many embeds are connected? HOT 4
- ERROR: No matching distribution found for nltk==7.1.2 HOT 3
- bdb.BdbQuit error while training conll 2003 HOT 1
- Error when loading custom dataset HOT 5
- Memory requirements for a new model HOT 3
- Segmentation Fault (core dumped) HOT 3
- Install fails all python versions tested 3.6 3.7 3.8 3.9 3.10 3.11. Repo Unusable.
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from ace.