End of training
Browse files- README.md +81 -0
- model.safetensors +1 -1
README.md
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---
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base_model: ylacombe/w2v-bert-2.0
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_16_0
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metrics:
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- wer
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model-index:
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- name: w2v-fine-tune-test-no-punct4
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: common_voice_16_0
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type: common_voice_16_0
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config: tr
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split: test
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args: tr
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metrics:
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- name: Wer
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type: wer
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value: 0.436
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# w2v-fine-tune-test-no-punct4
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This model is a fine-tuned version of [ylacombe/w2v-bert-2.0](https://huggingface.co/ylacombe/w2v-bert-2.0) on the common_voice_16_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7511
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- Wer: 0.436
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 20
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- num_epochs: 10
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-----:|
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| 4.367 | 1.54 | 20 | 3.3453 | 1.0 |
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| 2.1265 | 3.08 | 40 | 1.7730 | 0.996 |
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| 0.4755 | 4.62 | 60 | 0.8654 | 0.684 |
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| 0.203 | 6.15 | 80 | 0.7436 | 0.56 |
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| 0.1251 | 7.69 | 100 | 0.8143 | 0.548 |
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| 0.0449 | 9.23 | 120 | 0.7511 | 0.436 |
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### Framework versions
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- Transformers 4.37.0.dev0
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- Pytorch 2.1.0+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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