Commit
•
2a6c12f
1
Parent(s):
b2e04b7
Fixed tokenization and added test eval
Browse files- README.md +82 -89
- all_results.json +45 -31
- config.json +13 -13
- pytorch_model.bin +1 -1
- test_results.json +17 -0
- train_results.json +17 -0
- trainer_state.json +2215 -0
- training_args.bin +2 -2
- validation_results.json +17 -0
README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- wnut_17
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model-index:
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- name: fine_tune_bert_output
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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#
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This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Overall Precision: 0.
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- Overall Recall: 0.
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- Overall F1: 0.
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- Overall Accuracy: 0.
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- Corporation F1: 0.
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- Creative-work F1: 0.
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- Group F1: 0.
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- Location F1: 0.
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- Person F1: 0.
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- Product F1: 0.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 100
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Corporation F1 | Creative-work F1 | Group F1 | Location F1 | Person F1 | Product F1 |
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|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:--------:|:-----------:|:---------:|:----------:|
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.11.0+cu113
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- wnut_17
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model-index:
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- name: fine_tune_bert_output
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# fine_tune_bert_output
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This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the wnut_17 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3239
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- Overall Precision: 0.6913
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- Overall Recall: 0.5914
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- Overall F1: 0.6374
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- Overall Accuracy: 0.9499
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- Corporation F1: 0.2703
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- Creative-work F1: 0.3636
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- Group F1: 0.4030
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- Location F1: 0.7500
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- Person F1: 0.7733
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- Product F1: 0.4152
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 100
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Corporation F1 | Creative-work F1 | Group F1 | Location F1 | Person F1 | Product F1 |
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|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:--------:|:-----------:|:---------:|:----------:|
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| 0.2691 | 1.0 | 213 | 0.4035 | 0.0 | 0.0 | 0.0 | 0.8979 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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| 0.1604 | 2.0 | 426 | 0.3054 | 0.6255 | 0.4161 | 0.4998 | 0.9324 | 0.0 | 0.0 | 0.0 | 0.3534 | 0.6877 | 0.0 |
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| 0.1118 | 3.0 | 639 | 0.2864 | 0.6655 | 0.4643 | 0.5470 | 0.9404 | 0.1961 | 0.1164 | 0.1538 | 0.5803 | 0.7221 | 0.1865 |
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| 0.0524 | 4.0 | 852 | 0.2891 | 0.6945 | 0.5042 | 0.5842 | 0.9442 | 0.2017 | 0.3273 | 0.2472 | 0.6522 | 0.7366 | 0.2581 |
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| 0.0446 | 5.0 | 1065 | 0.2691 | 0.6815 | 0.5847 | 0.6294 | 0.9486 | 0.2737 | 0.3415 | 0.3007 | 0.6703 | 0.7768 | 0.3243 |
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| 0.0296 | 6.0 | 1278 | 0.2739 | 0.6740 | 0.5615 | 0.6126 | 0.9479 | 0.3065 | 0.3766 | 0.3333 | 0.7 | 0.7582 | 0.3472 |
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| 0.0261 | 7.0 | 1491 | 0.3150 | 0.6907 | 0.5415 | 0.6071 | 0.9457 | 0.2292 | 0.3350 | 0.304 | 0.6369 | 0.7547 | 0.2982 |
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| 0.0193 | 8.0 | 1704 | 0.2922 | 0.6957 | 0.5772 | 0.6310 | 0.9496 | 0.2887 | 0.3621 | 0.3676 | 0.7475 | 0.7645 | 0.4158 |
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| 0.0173 | 9.0 | 1917 | 0.2823 | 0.6845 | 0.5963 | 0.6374 | 0.9501 | 0.25 | 0.3863 | 0.3660 | 0.6729 | 0.7810 | 0.4064 |
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| 0.0227 | 10.0 | 2130 | 0.2912 | 0.6719 | 0.5681 | 0.6157 | 0.9482 | 0.2268 | 0.3797 | 0.3625 | 0.7045 | 0.7572 | 0.4286 |
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| 0.0185 | 11.0 | 2343 | 0.3140 | 0.6941 | 0.5598 | 0.6198 | 0.9482 | 0.2532 | 0.3896 | 0.3382 | 0.7059 | 0.7601 | 0.3961 |
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| 0.0221 | 12.0 | 2556 | 0.3527 | 0.6937 | 0.5473 | 0.6119 | 0.9470 | 0.3220 | 0.3687 | 0.35 | 0.7245 | 0.7502 | 0.3308 |
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| 0.0099 | 13.0 | 2769 | 0.3332 | 0.6872 | 0.5748 | 0.6260 | 0.9493 | 0.3168 | 0.3782 | 0.3597 | 0.7391 | 0.7627 | 0.4027 |
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| 0.0062 | 14.0 | 2982 | 0.3637 | 0.7287 | 0.5465 | 0.6246 | 0.9479 | 0.25 | 0.3700 | 0.4065 | 0.7340 | 0.7526 | 0.3468 |
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| 0.0075 | 15.0 | 3195 | 0.3239 | 0.6913 | 0.5914 | 0.6374 | 0.9499 | 0.2703 | 0.3636 | 0.4030 | 0.7500 | 0.7733 | 0.4152 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.11.0+cu113
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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all_results.json
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{
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"test_overall_precision": 0.6208362863217576,
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"validation_steps_per_second": 9.746
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}
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config.json
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"max_position_embeddings": 130,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"B-corporation": 1,
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"B-creative-work": 3,
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"B-group": 5,
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"B-location": 7,
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"B-person": 9,
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"I-creative-work": 4,
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"I-product": 12,
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"O": 0
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pytorch_model.bin
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test_results.json
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"epoch": 15.0,
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"test_corporation_f1": 0.22680412371134023,
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"test_creative-work_f1": 0.3375796178343949,
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"test_loss": 0.27450963854789734,
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"test_overall_accuracy": 0.9475309541150765,
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"test_overall_precision": 0.6208362863217576,
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"test_overall_recall": 0.4538860103626943,
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"test_person_f1": 0.6735751295336786,
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"test_product_f1": 0.1962264150943396,
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"test_runtime": 7.5404,
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"test_samples_per_second": 170.68,
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"test_steps_per_second": 10.742
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}
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train_results.json
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"epoch": 15.0,
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"train_corporation_f1": 0.8200972447325771,
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| 4 |
+
"train_creative-work_f1": 0.8151898734177214,
|
| 5 |
+
"train_group_f1": 0.8691358024691358,
|
| 6 |
+
"train_location_f1": 0.9257142857142856,
|
| 7 |
+
"train_loss": 0.03221079334616661,
|
| 8 |
+
"train_overall_accuracy": 0.9946731734139803,
|
| 9 |
+
"train_overall_f1": 0.8949512843224092,
|
| 10 |
+
"train_overall_precision": 0.884453781512605,
|
| 11 |
+
"train_overall_recall": 0.9057009680889208,
|
| 12 |
+
"train_person_f1": 0.9489291598023064,
|
| 13 |
+
"train_product_f1": 0.7822014051522247,
|
| 14 |
+
"train_runtime": 13.2179,
|
| 15 |
+
"train_samples_per_second": 256.773,
|
| 16 |
+
"train_steps_per_second": 16.114
|
| 17 |
+
}
|
trainer_state.json
ADDED
|
@@ -0,0 +1,2215 @@
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