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ft_wav2vec2_960h_thirty

Automatic Speech Recognition
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ImanNalia/FT_Wav2Vec2_960h_No_LM_V2

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  1. README.md +9 -9
  2. model.safetensors +1 -1
  3. runs/Apr07_07-37-47_n8ew6p6lio/events.out.tfevents.1712475558.n8ew6p6lio.50.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4593
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- - Wer: 39.9917
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- - Cer: 21.1881
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  ## Model description
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@@ -45,17 +45,17 @@ The following hyperparameters were used during training:
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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: 2000
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- - training_steps: 5000
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
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- | 4.9803 | 18.52 | 1000 | 2.7949 | 100.0 | 98.8206 |
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- | 1.1136 | 37.04 | 2000 | 1.2272 | 41.3621 | 21.5532 |
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- | 0.4547 | 55.56 | 3000 | 1.3323 | 41.2514 | 21.6285 |
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- | 0.2591 | 74.07 | 4000 | 1.3635 | 39.3688 | 20.8403 |
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- | 0.2232 | 92.59 | 5000 | 1.4593 | 39.9917 | 21.1881 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2440
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+ - Wer: 40.5592
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+ - Cer: 21.2837
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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: 2000
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+ - num_epochs: 50
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
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+ | 6.4178 | 9.26 | 500 | 3.0304 | 100.0 | 99.0785 |
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+ | 3.418 | 18.52 | 1000 | 2.9473 | 100.0 | 99.0785 |
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+ | 2.3895 | 27.78 | 1500 | 1.1051 | 47.8959 | 24.0394 |
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+ | 0.8914 | 37.04 | 2000 | 1.2159 | 43.2724 | 22.3298 |
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+ | 0.5237 | 46.3 | 2500 | 1.2440 | 40.5592 | 21.2837 |
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  ### Framework versions
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