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my_awesome_opus_books_model
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7142
- Bleu: 0.1327
- Gen Len: 11.4
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 1 | 10.1215 | 0.0 | 19.0 |
| No log | 2.0 | 2 | 10.1215 | 0.0 | 19.0 |
| No log | 3.0 | 3 | 10.1215 | 0.0 | 19.0 |
| No log | 4.0 | 4 | 9.9493 | 0.0 | 19.0 |
| No log | 5.0 | 5 | 9.7067 | 0.0 | 19.0 |
| No log | 6.0 | 6 | 9.5209 | 0.0 | 19.0 |
| No log | 7.0 | 7 | 9.1640 | 0.0 | 19.0 |
| No log | 8.0 | 8 | 9.1640 | 0.0 | 19.0 |
| No log | 9.0 | 9 | 8.9257 | 0.0 | 19.0 |
| No log | 10.0 | 10 | 8.7095 | 0.0 | 19.0 |
| No log | 11.0 | 11 | 8.0234 | 0.0 | 19.0 |
| No log | 12.0 | 12 | 7.6148 | 0.0 | 19.0 |
| No log | 13.0 | 13 | 7.6148 | 0.0 | 19.0 |
| No log | 14.0 | 14 | 7.3894 | 0.0 | 19.0 |
| No log | 15.0 | 15 | 7.1168 | 0.0 | 19.0 |
| No log | 16.0 | 16 | 6.9173 | 0.0 | 19.0 |
| No log | 17.0 | 17 | 6.7148 | 0.0 | 19.0 |
| No log | 18.0 | 18 | 6.3630 | 0.0 | 19.0 |
| No log | 19.0 | 19 | 6.0068 | 0.0 | 19.0 |
| No log | 20.0 | 20 | 5.8264 | 0.0 | 19.0 |
| No log | 21.0 | 21 | 5.6897 | 0.0 | 19.0 |
| No log | 22.0 | 22 | 5.5416 | 0.0 | 19.0 |
| No log | 23.0 | 23 | 5.4310 | 0.0 | 19.0 |
| No log | 24.0 | 24 | 5.3268 | 0.6787 | 19.0 |
| No log | 25.0 | 25 | 5.2214 | 2.6287 | 19.0 |
| No log | 26.0 | 26 | 5.0786 | 2.6287 | 19.0 |
| No log | 27.0 | 27 | 4.9850 | 3.2603 | 19.0 |
| No log | 28.0 | 28 | 4.9030 | 3.6542 | 19.0 |
| No log | 29.0 | 29 | 4.8184 | 3.6542 | 19.0 |
| No log | 30.0 | 30 | 4.7408 | 3.6542 | 19.0 |
| No log | 31.0 | 31 | 4.6692 | 3.6542 | 19.0 |
| No log | 32.0 | 32 | 4.5869 | 3.6542 | 19.0 |
| No log | 33.0 | 33 | 4.4861 | 3.6542 | 19.0 |
| No log | 34.0 | 34 | 4.3921 | 3.6542 | 19.0 |
| No log | 35.0 | 35 | 4.3102 | 3.6542 | 19.0 |
| No log | 36.0 | 36 | 4.2375 | 3.6542 | 19.0 |
| No log | 37.0 | 37 | 4.1691 | 3.6542 | 19.0 |
| No log | 38.0 | 38 | 4.1019 | 3.6542 | 19.0 |
| No log | 39.0 | 39 | 4.0349 | 3.6542 | 19.0 |
| No log | 40.0 | 40 | 3.9652 | 3.6542 | 19.0 |
| No log | 41.0 | 41 | 3.8937 | 3.6542 | 19.0 |
| No log | 42.0 | 42 | 3.8232 | 3.6542 | 19.0 |
| No log | 43.0 | 43 | 3.7526 | 3.6542 | 19.0 |
| No log | 44.0 | 44 | 3.6845 | 3.6542 | 19.0 |
| No log | 45.0 | 45 | 3.6196 | 3.6542 | 19.0 |
| No log | 46.0 | 46 | 3.5549 | 3.6542 | 19.0 |
| No log | 47.0 | 47 | 3.4897 | 3.6542 | 19.0 |
| No log | 48.0 | 48 | 3.4227 | 3.6542 | 19.0 |
| No log | 49.0 | 49 | 3.3559 | 3.6542 | 19.0 |
| No log | 50.0 | 50 | 3.2901 | 3.6542 | 19.0 |
| No log | 51.0 | 51 | 3.2237 | 3.6542 | 19.0 |
| No log | 52.0 | 52 | 3.1568 | 3.6542 | 19.0 |
| No log | 53.0 | 53 | 3.0880 | 3.6542 | 19.0 |
| No log | 54.0 | 54 | 3.0184 | 3.6542 | 19.0 |
| No log | 55.0 | 55 | 2.9428 | 3.6542 | 19.0 |
| No log | 56.0 | 56 | 2.8787 | 3.6542 | 19.0 |
| No log | 57.0 | 57 | 2.8177 | 3.6542 | 19.0 |
| No log | 58.0 | 58 | 2.7606 | 3.6542 | 19.0 |
| No log | 59.0 | 59 | 2.7053 | 3.6542 | 19.0 |
| No log | 60.0 | 60 | 2.6458 | 3.6542 | 19.0 |
| No log | 61.0 | 61 | 2.5915 | 3.6542 | 19.0 |
| No log | 62.0 | 62 | 2.5416 | 3.6542 | 19.0 |
| No log | 63.0 | 63 | 2.4929 | 3.6542 | 19.0 |
| No log | 64.0 | 64 | 2.4465 | 3.6542 | 19.0 |
| No log | 65.0 | 65 | 2.4007 | 3.6542 | 19.0 |
| No log | 66.0 | 66 | 2.3560 | 3.6542 | 19.0 |
| No log | 67.0 | 67 | 2.3136 | 3.6542 | 19.0 |
| No log | 68.0 | 68 | 2.2712 | 3.6542 | 19.0 |
| No log | 69.0 | 69 | 2.2313 | 3.6542 | 19.0 |
| No log | 70.0 | 70 | 2.1924 | 3.6542 | 19.0 |
| No log | 71.0 | 71 | 2.1563 | 3.6542 | 19.0 |
| No log | 72.0 | 72 | 2.1213 | 3.6542 | 19.0 |
| No log | 73.0 | 73 | 2.0885 | 3.6542 | 19.0 |
| No log | 74.0 | 74 | 2.0577 | 3.6542 | 19.0 |
| No log | 75.0 | 75 | 2.0293 | 3.6542 | 19.0 |
| No log | 76.0 | 76 | 2.0023 | 3.6542 | 19.0 |
| No log | 77.0 | 77 | 1.9762 | 3.6542 | 19.0 |
| No log | 78.0 | 78 | 1.9514 | 3.6542 | 19.0 |
| No log | 79.0 | 79 | 1.9288 | 3.6542 | 19.0 |
| No log | 80.0 | 80 | 1.9076 | 3.6542 | 19.0 |
| No log | 81.0 | 81 | 1.8876 | 3.6542 | 19.0 |
| No log | 82.0 | 82 | 1.8691 | 3.6542 | 19.0 |
| No log | 83.0 | 83 | 1.8520 | 3.6542 | 19.0 |
| No log | 84.0 | 84 | 1.8362 | 3.6542 | 19.0 |
| No log | 85.0 | 85 | 1.8217 | 1.2446 | 15.2 |
| No log | 86.0 | 86 | 1.8080 | 1.2446 | 15.2 |
| No log | 87.0 | 87 | 1.7957 | 0.1327 | 11.4 |
| No log | 88.0 | 88 | 1.7846 | 0.1327 | 11.4 |
| No log | 89.0 | 89 | 1.7743 | 0.1327 | 11.4 |
| No log | 90.0 | 90 | 1.7651 | 0.1327 | 11.4 |
| No log | 91.0 | 91 | 1.7569 | 0.1327 | 11.4 |
| No log | 92.0 | 92 | 1.7493 | 0.1327 | 11.4 |
| No log | 93.0 | 93 | 1.7426 | 0.1327 | 11.4 |
| No log | 94.0 | 94 | 1.7367 | 0.1327 | 11.4 |
| No log | 95.0 | 95 | 1.7320 | 0.1327 | 11.4 |
| No log | 96.0 | 96 | 1.7273 | 0.1327 | 11.4 |
| No log | 97.0 | 97 | 1.7235 | 0.1327 | 11.4 |
| No log | 98.0 | 98 | 1.7200 | 0.1327 | 11.4 |
| No log | 99.0 | 99 | 1.7170 | 0.1327 | 11.4 |
| No log | 100.0 | 100 | 1.7142 | 0.1327 | 11.4 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
