bert_uncased_L-2_H-512_A-8_mnli
This model is a fine-tuned version of google/bert_uncased_L-2_H-512_A-8 on the GLUE MNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6203
- Accuracy: 0.7480
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: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.7818 | 1.0 | 1534 | 0.6984 | 0.6953 |
0.6602 | 2.0 | 3068 | 0.6456 | 0.7317 |
0.595 | 3.0 | 4602 | 0.6422 | 0.7429 |
0.5414 | 4.0 | 6136 | 0.6632 | 0.7442 |
0.4938 | 5.0 | 7670 | 0.6538 | 0.7492 |
0.4493 | 6.0 | 9204 | 0.6956 | 0.7489 |
0.4103 | 7.0 | 10738 | 0.6977 | 0.7489 |
0.3738 | 8.0 | 12272 | 0.7407 | 0.7434 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3
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Base model
google/bert_uncased_L-2_H-512_A-8