DNADebertaSentencepiece10k_continuation_continuation
This model is a fine-tuned version of Vlasta/DNADebertaSentencepiece10k_continuation on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.3056
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.4806 | 0.36 | 5000 | 5.4385 |
| 5.4848 | 0.72 | 10000 | 5.4333 |
| 5.4803 | 1.08 | 15000 | 5.4312 |
| 5.4759 | 1.45 | 20000 | 5.4223 |
| 5.4703 | 1.81 | 25000 | 5.4199 |
| 5.4626 | 2.17 | 30000 | 5.4147 |
| 5.4596 | 2.53 | 35000 | 5.4094 |
| 5.4534 | 2.89 | 40000 | 5.4014 |
| 5.4466 | 3.25 | 45000 | 5.4017 |
| 5.445 | 3.61 | 50000 | 5.3954 |
| 5.4446 | 3.97 | 55000 | 5.3916 |
| 5.4359 | 4.34 | 60000 | 5.3809 |
| 5.4327 | 4.7 | 65000 | 5.3846 |
| 5.4281 | 5.06 | 70000 | 5.3765 |
| 5.4207 | 5.42 | 75000 | 5.3744 |
| 5.4207 | 5.78 | 80000 | 5.3704 |
| 5.4167 | 6.14 | 85000 | 5.3685 |
| 5.41 | 6.5 | 90000 | 5.3641 |
| 5.4117 | 6.86 | 95000 | 5.3582 |
| 5.4075 | 7.23 | 100000 | 5.3568 |
| 5.4017 | 7.59 | 105000 | 5.3547 |
| 5.4006 | 7.95 | 110000 | 5.3494 |
| 5.3969 | 8.31 | 115000 | 5.3475 |
| 5.3935 | 8.67 | 120000 | 5.3453 |
| 5.3926 | 9.03 | 125000 | 5.3422 |
| 5.3895 | 9.39 | 130000 | 5.3351 |
| 5.3813 | 9.75 | 135000 | 5.3326 |
| 5.3841 | 10.12 | 140000 | 5.3340 |
| 5.3787 | 10.48 | 145000 | 5.3301 |
| 5.3781 | 10.84 | 150000 | 5.3280 |
| 5.3769 | 11.2 | 155000 | 5.3258 |
| 5.3733 | 11.56 | 160000 | 5.3198 |
| 5.3683 | 11.92 | 165000 | 5.3180 |
| 5.3682 | 12.28 | 170000 | 5.3181 |
| 5.3673 | 12.64 | 175000 | 5.3167 |
| 5.3623 | 13.01 | 180000 | 5.3116 |
| 5.3602 | 13.37 | 185000 | 5.3109 |
| 5.361 | 13.73 | 190000 | 5.3071 |
| 5.3573 | 14.09 | 195000 | 5.3078 |
| 5.3575 | 14.45 | 200000 | 5.3051 |
| 5.3544 | 14.81 | 205000 | 5.3038 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1
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