distilbert_oscarth_0040
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 1.2890
- Validation Loss: 1.2296
- Epoch: 39
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
Train Loss | Validation Loss | Epoch |
---|---|---|
4.1327 | 2.9983 | 0 |
2.7813 | 2.4562 | 1 |
2.4194 | 2.2066 | 2 |
2.2231 | 2.0562 | 3 |
2.0894 | 1.9450 | 4 |
1.9905 | 1.8621 | 5 |
1.9148 | 1.7941 | 6 |
1.8508 | 1.7363 | 7 |
1.7976 | 1.6909 | 8 |
1.7509 | 1.6488 | 9 |
1.7126 | 1.6124 | 10 |
1.6764 | 1.5835 | 11 |
1.6450 | 1.5521 | 12 |
1.6175 | 1.5282 | 13 |
1.5919 | 1.5045 | 14 |
1.5679 | 1.4833 | 15 |
1.5476 | 1.4627 | 16 |
1.5271 | 1.4498 | 17 |
1.5098 | 1.4270 | 18 |
1.4909 | 1.4161 | 19 |
1.4760 | 1.3995 | 20 |
1.4609 | 1.3864 | 21 |
1.4475 | 1.3717 | 22 |
1.4333 | 1.3590 | 23 |
1.4203 | 1.3478 | 24 |
1.4093 | 1.3403 | 25 |
1.3980 | 1.3296 | 26 |
1.3875 | 1.3176 | 27 |
1.3773 | 1.3094 | 28 |
1.3674 | 1.3011 | 29 |
1.3579 | 1.2920 | 30 |
1.3497 | 1.2826 | 31 |
1.3400 | 1.2764 | 32 |
1.3326 | 1.2694 | 33 |
1.3236 | 1.2635 | 34 |
1.3169 | 1.2536 | 35 |
1.3096 | 1.2477 | 36 |
1.3024 | 1.2408 | 37 |
1.2957 | 1.2364 | 38 |
1.2890 | 1.2296 | 39 |
Framework versions
- Transformers 4.20.1
- TensorFlow 2.8.2
- Datasets 2.3.2
- Tokenizers 0.12.1
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