End of training
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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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base_model: facebook/w2v-bert-2.0
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datasets:
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- generator
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metrics:
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- name: wav2vec2-bert-fon
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results:
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- task:
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type: automatic-speech-recognition
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name: Automatic Speech Recognition
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dataset:
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name: generator
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type: generator
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split: train
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args: default
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metrics:
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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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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the generator dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer: 0.
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## Model description
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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: 500
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- num_epochs:
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- mixed_precision_training: Native AMP
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### Training results
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### Framework versions
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---
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license: mit
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base_model: facebook/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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- generator
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metrics:
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- name: wav2vec2-bert-fon
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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: generator
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type: generator
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split: train
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args: default
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metrics:
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- name: Wer
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type: wer
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value: 0.17488323819408408
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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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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the generator dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2409
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- Wer: 0.1749
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## Model description
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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: 500
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- num_epochs: 4
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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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| No log | 0.18 | 250 | 1.2212 | 0.8079 |
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| 2.1756 | 0.35 | 500 | 0.6697 | 0.6058 |
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| 2.1756 | 0.53 | 750 | 0.5137 | 0.4606 |
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| 0.5041 | 0.7 | 1000 | 0.4337 | 0.4234 |
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| 0.5041 | 0.88 | 1250 | 0.3452 | 0.3529 |
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| 0.426 | 1.05 | 1500 | 0.2770 | 0.2910 |
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| 0.426 | 1.23 | 1750 | 0.2681 | 0.2439 |
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| 0.2916 | 1.4 | 2000 | 0.2423 | 0.2155 |
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| 0.2916 | 1.58 | 2250 | 0.2342 | 0.2077 |
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| 0.2591 | 1.75 | 2500 | 0.1986 | 0.1791 |
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| 0.2591 | 1.93 | 2750 | 0.1864 | 0.1597 |
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| 0.2261 | 2.1 | 3000 | 0.1712 | 0.1419 |
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| 0.2261 | 2.28 | 3250 | 0.1786 | 0.1497 |
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| 0.1564 | 2.45 | 3500 | 0.1612 | 0.1324 |
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| 0.1564 | 2.63 | 3750 | 0.1730 | 0.1591 |
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| 0.1542 | 2.8 | 4000 | 0.1558 | 0.1364 |
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| 0.1542 | 2.98 | 4250 | 0.1493 | 0.1581 |
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| 0.1559 | 3.15 | 4500 | 0.1489 | 0.1347 |
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| 0.1559 | 3.33 | 4750 | 0.2036 | 0.1486 |
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| 0.1992 | 3.5 | 5000 | 0.2644 | 0.1582 |
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| 0.1992 | 3.68 | 5250 | 0.2401 | 0.1878 |
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| 0.291 | 3.85 | 5500 | 0.2409 | 0.1749 |
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### Framework versions
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model.safetensors
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runs/Jun20_23-33-44_05e8c5fb976b/events.out.tfevents.1718926633.05e8c5fb976b.24.0
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