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mascir_fr_hubert_test
This model is a fine-tuned version of facebook/hubert-large-ls960-ft on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0113
- Wer: 0.1680
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
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 8.06 | 250 | 3.0885 | 0.9919 |
| 5.8634 | 16.13 | 500 | 2.8476 | 0.9919 |
| 5.8634 | 24.19 | 750 | 1.1091 | 0.9461 |
| 1.7302 | 32.26 | 1000 | 0.4035 | 0.6076 |
| 1.7302 | 40.32 | 1250 | 0.1643 | 0.3980 |
| 0.5446 | 48.39 | 1500 | 0.0872 | 0.2784 |
| 0.5446 | 56.45 | 1750 | 0.0464 | 0.2257 |
| 0.3144 | 64.52 | 2000 | 0.0311 | 0.2021 |
| 0.3144 | 72.58 | 2250 | 0.0213 | 0.1891 |
| 0.2224 | 80.65 | 2500 | 0.0155 | 0.1816 |
| 0.2224 | 88.71 | 2750 | 0.0132 | 0.1699 |
| 0.1871 | 96.77 | 3000 | 0.0113 | 0.1680 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3
