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fineTunning3
RAF3197/fineTunning3
fineTunning3 is a machine learning model from RAF3197. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Nov 22, 2024
- Updated
- Nov 24, 2024
- SHA
- 335cbbf9
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
fineTunning3
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7642
- Wer: 1.0100
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
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 40
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 4.03 | 250 | 12.8710 | 1.0 |
| 7.1272 | 8.06 | 500 | 3.4483 | 1.0 |
| 7.1272 | 12.1 | 750 | 3.0834 | 1.0 |
| 2.9944 | 16.13 | 1000 | 3.0052 | 1.0 |
| 2.9944 | 20.16 | 1250 | 2.8564 | 1.0 |
| 2.7966 | 24.19 | 1500 | 2.6613 | 1.0 |
| 2.7966 | 28.22 | 1750 | 2.3765 | 1.0 |
| 2.4567 | 32.26 | 2000 | 2.0220 | 1.0089 |
| 2.4567 | 36.29 | 2250 | 1.7642 | 1.0100 |
Framework versions
- Transformers 4.17.0
- Pytorch 2.5.1+cu118
- Datasets 1.18.3
- Tokenizers 0.20.3
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Nov 22, 2024
- Updated
- Nov 24, 2024