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t5-small_6_3-en-hi_en_LinCE
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2034
- Bleu: 7.8135
- Gen Len: 39.5564
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 0.99 | 94 | 3.5424 | 0.9187 | 16.7437 |
| No log | 1.99 | 188 | 3.1434 | 1.2886 | 16.8158 |
| No log | 2.99 | 282 | 2.9494 | 1.4577 | 16.7824 |
| No log | 3.99 | 376 | 2.8233 | 1.4745 | 16.8879 |
| No log | 4.99 | 470 | 2.7300 | 1.7116 | 16.6636 |
| 3.6303 | 5.99 | 564 | 2.6589 | 1.7857 | 16.6302 |
| 3.6303 | 6.99 | 658 | 2.6005 | 1.8572 | 16.4553 |
| 3.6303 | 7.99 | 752 | 2.5456 | 2.139 | 16.3925 |
| 3.6303 | 8.99 | 846 | 2.5023 | 2.3835 | 16.2911 |
| 3.6303 | 9.99 | 940 | 2.4725 | 2.5607 | 16.3271 |
| 2.9087 | 10.99 | 1034 | 2.4272 | 2.6614 | 16.3138 |
| 2.9087 | 11.99 | 1128 | 2.3977 | 2.9623 | 16.3338 |
| 2.9087 | 12.99 | 1222 | 2.3686 | 3.1248 | 16.2443 |
| 2.9087 | 13.99 | 1316 | 2.3438 | 3.3294 | 16.3458 |
| 2.9087 | 14.99 | 1410 | 2.3253 | 3.3885 | 16.3591 |
| 2.6588 | 15.99 | 1504 | 2.3028 | 3.3985 | 16.3124 |
| 2.6588 | 16.99 | 1598 | 2.2839 | 3.3772 | 16.3858 |
| 2.6588 | 17.99 | 1692 | 2.2704 | 3.5804 | 16.3872 |
| 2.6588 | 18.99 | 1786 | 2.2533 | 3.8751 | 16.2697 |
| 2.6588 | 19.99 | 1880 | 2.2378 | 4.0003 | 16.3271 |
| 2.6588 | 20.99 | 1974 | 2.2233 | 4.0271 | 16.3031 |
| 2.5079 | 21.99 | 2068 | 2.2160 | 4.1898 | 16.3057 |
| 2.5079 | 22.99 | 2162 | 2.2010 | 4.1216 | 16.3031 |
| 2.5079 | 23.99 | 2256 | 2.1935 | 4.1311 | 16.2644 |
| 2.5079 | 24.99 | 2350 | 2.1833 | 4.1373 | 16.3138 |
| 2.5079 | 25.99 | 2444 | 2.1725 | 4.3471 | 16.3057 |
| 2.4027 | 26.99 | 2538 | 2.1657 | 4.183 | 16.3298 |
| 2.4027 | 27.99 | 2632 | 2.1611 | 4.2867 | 16.3351 |
| 2.4027 | 28.99 | 2726 | 2.1531 | 4.2689 | 16.2737 |
| 2.4027 | 29.99 | 2820 | 2.1482 | 4.4802 | 16.2644 |
| 2.4027 | 30.99 | 2914 | 2.1443 | 4.469 | 16.231 |
| 2.3251 | 31.99 | 3008 | 2.1375 | 4.5295 | 16.227 |
| 2.3251 | 32.99 | 3102 | 2.1330 | 4.4799 | 16.2243 |
| 2.3251 | 33.99 | 3196 | 2.1307 | 4.7124 | 16.2417 |
| 2.3251 | 34.99 | 3290 | 2.1248 | 4.5954 | 16.3004 |
| 2.3251 | 35.99 | 3384 | 2.1215 | 4.7455 | 16.215 |
| 2.3251 | 36.99 | 3478 | 2.1166 | 4.6233 | 16.2016 |
| 2.2818 | 37.99 | 3572 | 2.1147 | 4.6843 | 16.219 |
| 2.2818 | 38.99 | 3666 | 2.1112 | 4.7068 | 16.2163 |
| 2.2818 | 39.99 | 3760 | 2.1071 | 4.684 | 16.223 |
| 2.2818 | 40.99 | 3854 | 2.1034 | 4.7323 | 16.2523 |
| 2.2818 | 41.99 | 3948 | 2.0998 | 4.6406 | 16.2016 |
| 2.2392 | 42.99 | 4042 | 2.1017 | 4.7609 | 16.1976 |
| 2.2392 | 43.99 | 4136 | 2.1021 | 4.7634 | 16.2069 |
| 2.2392 | 44.99 | 4230 | 2.0994 | 4.7854 | 16.1976 |
| 2.2392 | 45.99 | 4324 | 2.0980 | 4.7562 | 16.2243 |
| 2.2392 | 46.99 | 4418 | 2.0964 | 4.7921 | 16.219 |
| 2.2192 | 47.99 | 4512 | 2.0970 | 4.8029 | 16.2377 |
| 2.2192 | 48.99 | 4606 | 2.0967 | 4.7953 | 16.2176 |
| 2.2192 | 49.99 | 4700 | 2.0968 | 4.819 | 16.2457 |
Framework versions
- Transformers 4.20.0.dev0
- Pytorch 1.8.0
- Datasets 2.1.0
- Tokenizers 0.12.1
