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bart-large-mnli-aitools-8n
This model is a fine-tuned version of facebook/bart-large-mnli on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2700
- Accuracy: 0.9630
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: 4
- eval_batch_size: 4
- 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 | 0.07 | 50 | 0.5082 | 0.8580 |
No log | 0.14 | 100 | 0.5312 | 0.8580 |
No log | 0.21 | 150 | 0.3020 | 0.9259 |
No log | 0.27 | 200 | 0.3802 | 0.9259 |
No log | 0.34 | 250 | 0.3721 | 0.9259 |
No log | 0.41 | 300 | 0.3692 | 0.9321 |
No log | 0.48 | 350 | 0.4657 | 0.8951 |
No log | 0.55 | 400 | 0.5192 | 0.9198 |
No log | 0.62 | 450 | 0.4348 | 0.9259 |
0.3718 | 0.68 | 500 | 0.3369 | 0.9383 |
0.3718 | 0.75 | 550 | 0.3150 | 0.9444 |
0.3718 | 0.82 | 600 | 0.2712 | 0.9630 |
0.3718 | 0.89 | 650 | 0.2900 | 0.9444 |
0.3718 | 0.96 | 700 | 0.2895 | 0.9444 |
0.3718 | 1.03 | 750 | 0.2578 | 0.9383 |
0.3718 | 1.09 | 800 | 0.3731 | 0.9506 |
0.3718 | 1.16 | 850 | 0.1916 | 0.9506 |
0.3718 | 1.23 | 900 | 0.1980 | 0.9444 |
0.3718 | 1.3 | 950 | 0.3446 | 0.9506 |
0.2003 | 1.37 | 1000 | 0.3997 | 0.9444 |
0.2003 | 1.44 | 1050 | 0.3500 | 0.9444 |
0.2003 | 1.5 | 1100 | 0.2820 | 0.9444 |
0.2003 | 1.57 | 1150 | 0.3192 | 0.9506 |
0.2003 | 1.64 | 1200 | 0.3207 | 0.9444 |
0.2003 | 1.71 | 1250 | 0.2535 | 0.9444 |
0.2003 | 1.78 | 1300 | 0.2543 | 0.9506 |
0.2003 | 1.85 | 1350 | 0.2218 | 0.9691 |
0.2003 | 1.92 | 1400 | 0.3685 | 0.9444 |
0.2003 | 1.98 | 1450 | 0.2633 | 0.9630 |
0.1534 | 2.05 | 1500 | 0.2700 | 0.9630 |
0.1534 | 2.12 | 1550 | 0.1888 | 0.9568 |
0.1534 | 2.19 | 1600 | 0.2366 | 0.9630 |
0.1534 | 2.26 | 1650 | 0.2998 | 0.9630 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2