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assignment2_meher_test2
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5440
- Precision: 0.2070
- Recall: 0.2440
- F1: 0.2240
- Accuracy: 0.9244
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 347 | 0.2833 | 0.1672 | 0.1787 | 0.1728 | 0.9252 |
| 0.2912 | 2.0 | 694 | 0.3104 | 0.1923 | 0.2062 | 0.1990 | 0.9262 |
| 0.1166 | 3.0 | 1041 | 0.3258 | 0.1973 | 0.2474 | 0.2195 | 0.9235 |
| 0.1166 | 4.0 | 1388 | 0.3608 | 0.1818 | 0.3024 | 0.2271 | 0.9131 |
| 0.054 | 5.0 | 1735 | 0.4753 | 0.2093 | 0.2165 | 0.2128 | 0.9239 |
| 0.0277 | 6.0 | 2082 | 0.4959 | 0.2181 | 0.2405 | 0.2288 | 0.9246 |
| 0.0277 | 7.0 | 2429 | 0.5534 | 0.2331 | 0.1890 | 0.2087 | 0.9309 |
| 0.0159 | 8.0 | 2776 | 0.5215 | 0.2281 | 0.2509 | 0.2390 | 0.9254 |
| 0.0091 | 9.0 | 3123 | 0.5522 | 0.2244 | 0.2405 | 0.2322 | 0.9256 |
| 0.0091 | 10.0 | 3470 | 0.5440 | 0.2070 | 0.2440 | 0.2240 | 0.9244 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
