run_2
This model is a fine-tuned version of bert-base-uncased on the wikitext dataset. It achieves the following results on the evaluation set:
- Loss: 0.9502
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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
8.4559 | 0.27 | 50 | 7.1236 |
6.8523 | 0.55 | 100 | 6.6676 |
6.6103 | 0.82 | 150 | 6.5582 |
6.2417 | 1.1 | 200 | 5.6994 |
4.9738 | 1.37 | 250 | 4.3440 |
4.1043 | 1.65 | 300 | 3.7804 |
3.4265 | 1.92 | 350 | 3.0136 |
2.7667 | 2.2 | 400 | 2.5318 |
2.3538 | 2.47 | 450 | 2.0903 |
1.9591 | 2.75 | 500 | 1.7367 |
1.6652 | 3.02 | 550 | 1.5016 |
1.4318 | 3.29 | 600 | 1.3162 |
1.275 | 3.57 | 650 | 1.1657 |
1.1553 | 3.84 | 700 | 1.0655 |
1.0629 | 4.12 | 750 | 1.0029 |
1.0029 | 4.39 | 800 | 0.9683 |
0.9881 | 4.67 | 850 | 0.9536 |
0.9779 | 4.94 | 900 | 0.9502 |
Framework versions
- Transformers 4.33.1
- Pytorch 1.12.1
- Datasets 2.14.6
- Tokenizers 0.13.3
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