ckpts
This model is a fine-tuned version of facebook/hubert-base-ls960 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2980
- Accuracy: 0.9545
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.1628 | 1.0 | 223 | 0.7126 | 0.7727 |
0.6562 | 2.0 | 446 | 0.5069 | 0.8485 |
0.4199 | 3.0 | 669 | 0.3570 | 0.8990 |
0.325 | 4.0 | 892 | 0.2092 | 0.9394 |
0.2217 | 5.0 | 1115 | 0.2392 | 0.9444 |
0.1831 | 6.0 | 1338 | 0.2754 | 0.9293 |
0.1598 | 7.0 | 1561 | 0.3294 | 0.9343 |
0.1676 | 8.0 | 1784 | 0.2669 | 0.9495 |
0.1597 | 9.0 | 2007 | 0.3438 | 0.9293 |
0.1132 | 10.0 | 2230 | 0.3159 | 0.9444 |
0.1224 | 11.0 | 2453 | 0.2980 | 0.9545 |
0.095 | 12.0 | 2676 | 0.2970 | 0.9444 |
0.1087 | 13.0 | 2899 | 0.3449 | 0.9343 |
0.1254 | 14.0 | 3122 | 0.3198 | 0.9444 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for Gizachew/ckpts
Base model
facebook/hubert-base-ls960