autotrain-model-datasaur-NWMxYjJhNGI-NzgzYTFlMzc
This model is a fine-tuned version of bert-base-uncased on the datasaur-nw_mx_yj_jh_ngi-nzgz_yt_fl_mzc dataset. It achieves the following results on the evaluation set:
- Loss: 1.0631
- Accuracy: 0.81
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: 0.0001
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 50 | 0.9662 | 0.57 |
| No log | 2.0 | 100 | 0.6139 | 0.81 |
| No log | 3.0 | 150 | 1.0690 | 0.73 |
| No log | 4.0 | 200 | 1.0106 | 0.8 |
| No log | 5.0 | 250 | 1.0631 | 0.81 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for datasaur-dev/autotrain-model-datasaur-NWMxYjJhNGI-NzgzYTFlMzc
Base model
google-bert/bert-base-uncasedEvaluation results
- Accuracy on datasaur-nw_mx_yj_jh_ngi-nzgz_yt_fl_mzcvalidation set self-reported0.810