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Text Classification
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distilbert
Generated from Trainer
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End of training

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  1. README.md +70 -10
  2. model.safetensors +1 -1
  3. runs/Mar13_21-22-02_4931855db211/events.out.tfevents.1710364950.4931855db211.166.0 +3 -0
  4. runs/Mar13_21-22-02_4931855db211/events.out.tfevents.1710371000.4931855db211.166.1 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -3,6 +3,11 @@ license: apache-2.0
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  base_model: distilbert-base-cased
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  tags:
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  - generated_from_trainer
 
 
 
 
 
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  model-index:
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  - name: trainer10
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  results: []
@@ -15,15 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - eval_loss: 1.9534
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- - eval_precision: 0.0212
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- - eval_recall: 0.1429
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- - eval_f1: 0.0369
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- - eval_accuracy: 0.1429
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- - eval_runtime: 5.0122
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- - eval_samples_per_second: 16.759
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- - eval_steps_per_second: 2.195
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- - step: 0
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  ## Model description
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@@ -50,9 +51,68 @@ The following hyperparameters were used during training:
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  - lr_scheduler_type: linear
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  - num_epochs: 30
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  ### Framework versions
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  - Transformers 4.38.2
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- - Pytorch 2.1.0+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
 
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  base_model: distilbert-base-cased
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  tags:
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  - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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  model-index:
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  - name: trainer10
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  results: []
 
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  This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.8784
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+ - Precision: 0.6554
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+ - Recall: 0.6310
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+ - F1: 0.6226
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+ - Accuracy: 0.6310
 
 
 
 
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  ## Model description
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  - lr_scheduler_type: linear
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  - num_epochs: 30
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 1.9269 | 0.57 | 30 | 1.8819 | 0.1351 | 0.2619 | 0.1571 | 0.2619 |
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+ | 1.8323 | 1.13 | 60 | 1.7729 | 0.2460 | 0.3571 | 0.2779 | 0.3571 |
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+ | 1.6414 | 1.7 | 90 | 1.5696 | 0.5043 | 0.4524 | 0.4074 | 0.4524 |
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+ | 1.3837 | 2.26 | 120 | 1.3431 | 0.3511 | 0.4762 | 0.3854 | 0.4762 |
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+ | 1.0816 | 2.83 | 150 | 1.1919 | 0.4576 | 0.5119 | 0.4623 | 0.5119 |
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+ | 0.7562 | 3.4 | 180 | 1.1171 | 0.5228 | 0.5357 | 0.4846 | 0.5357 |
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+ | 0.5875 | 3.96 | 210 | 1.0354 | 0.5617 | 0.5238 | 0.5181 | 0.5238 |
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+ | 0.3318 | 4.53 | 240 | 1.0221 | 0.6131 | 0.5833 | 0.5768 | 0.5833 |
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+ | 0.2607 | 5.09 | 270 | 1.0985 | 0.5913 | 0.5714 | 0.5584 | 0.5714 |
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+ | 0.1437 | 5.66 | 300 | 1.0669 | 0.5715 | 0.5476 | 0.5467 | 0.5476 |
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+ | 0.0846 | 6.23 | 330 | 1.1989 | 0.6190 | 0.5952 | 0.5936 | 0.5952 |
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+ | 0.0525 | 6.79 | 360 | 1.2240 | 0.6118 | 0.5952 | 0.5882 | 0.5952 |
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+ | 0.0494 | 7.36 | 390 | 1.3884 | 0.6320 | 0.5833 | 0.5797 | 0.5833 |
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+ | 0.0174 | 7.92 | 420 | 1.3464 | 0.6261 | 0.5952 | 0.5972 | 0.5952 |
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+ | 0.0124 | 8.49 | 450 | 1.4157 | 0.6466 | 0.6190 | 0.6059 | 0.6190 |
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+ | 0.0091 | 9.06 | 480 | 1.5045 | 0.6425 | 0.6071 | 0.6035 | 0.6071 |
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+ | 0.0081 | 9.62 | 510 | 1.5286 | 0.6489 | 0.6190 | 0.6131 | 0.6190 |
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+ | 0.0064 | 10.19 | 540 | 1.5502 | 0.6477 | 0.6190 | 0.6126 | 0.6190 |
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+ | 0.0057 | 10.75 | 570 | 1.5541 | 0.6394 | 0.6071 | 0.6030 | 0.6071 |
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+ | 0.0057 | 11.32 | 600 | 1.6535 | 0.6596 | 0.6310 | 0.6232 | 0.6310 |
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+ | 0.0047 | 11.89 | 630 | 1.6403 | 0.6436 | 0.6190 | 0.6053 | 0.6190 |
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+ | 0.0043 | 12.45 | 660 | 1.6434 | 0.6489 | 0.6190 | 0.6131 | 0.6190 |
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+ | 0.0039 | 13.02 | 690 | 1.6630 | 0.6507 | 0.6190 | 0.6188 | 0.6190 |
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+ | 0.0036 | 13.58 | 720 | 1.6792 | 0.6482 | 0.6190 | 0.6133 | 0.6190 |
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+ | 0.003 | 14.15 | 750 | 1.7049 | 0.6482 | 0.6190 | 0.6133 | 0.6190 |
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+ | 0.0031 | 14.72 | 780 | 1.7068 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0031 | 15.28 | 810 | 1.7272 | 0.6482 | 0.6190 | 0.6133 | 0.6190 |
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+ | 0.0028 | 15.85 | 840 | 1.7443 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0026 | 16.42 | 870 | 1.7604 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0024 | 16.98 | 900 | 1.7654 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0023 | 17.55 | 930 | 1.7699 | 0.6482 | 0.6190 | 0.6133 | 0.6190 |
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+ | 0.0023 | 18.11 | 960 | 1.7929 | 0.6394 | 0.6071 | 0.6030 | 0.6071 |
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+ | 0.0022 | 18.68 | 990 | 1.7985 | 0.6482 | 0.6190 | 0.6133 | 0.6190 |
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+ | 0.0021 | 19.25 | 1020 | 1.8119 | 0.6482 | 0.6190 | 0.6133 | 0.6190 |
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+ | 0.002 | 19.81 | 1050 | 1.8096 | 0.6394 | 0.6071 | 0.6030 | 0.6071 |
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+ | 0.0019 | 20.38 | 1080 | 1.8147 | 0.6496 | 0.6190 | 0.6128 | 0.6190 |
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+ | 0.0019 | 20.94 | 1110 | 1.8211 | 0.6496 | 0.6190 | 0.6128 | 0.6190 |
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+ | 0.0018 | 21.51 | 1140 | 1.8306 | 0.6394 | 0.6071 | 0.6030 | 0.6071 |
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+ | 0.0019 | 22.08 | 1170 | 1.8381 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0017 | 22.64 | 1200 | 1.8399 | 0.6394 | 0.6071 | 0.6030 | 0.6071 |
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+ | 0.0017 | 23.21 | 1230 | 1.8466 | 0.6394 | 0.6071 | 0.6030 | 0.6071 |
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+ | 0.0016 | 23.77 | 1260 | 1.8503 | 0.6470 | 0.6190 | 0.6128 | 0.6190 |
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+ | 0.0016 | 24.34 | 1290 | 1.8566 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0016 | 24.91 | 1320 | 1.8693 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0016 | 25.47 | 1350 | 1.8760 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0016 | 26.04 | 1380 | 1.8769 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0015 | 26.6 | 1410 | 1.8804 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0014 | 27.17 | 1440 | 1.8800 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0014 | 27.74 | 1470 | 1.8793 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0014 | 28.3 | 1500 | 1.8792 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0015 | 28.87 | 1530 | 1.8774 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0014 | 29.43 | 1560 | 1.8780 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+ | 0.0014 | 30.0 | 1590 | 1.8784 | 0.6554 | 0.6310 | 0.6226 | 0.6310 |
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+
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+
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  ### Framework versions
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  - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
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