janaab commited on
Commit
48f9278
1 Parent(s): faabfb9

End of training

Browse files
README.md CHANGED
@@ -7,13 +7,6 @@ tags:
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  model-index:
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  - name: whisper-small-sc
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  results: []
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- datasets:
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- - janaab/supreme-court-speech
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- language:
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- - en
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- metrics:
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- - wer
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- pipeline_tag: automatic-speech-recognition
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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
@@ -21,16 +14,16 @@ should probably proofread and complete it, then remove this comment. -->
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  # whisper-small-sc
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- This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on [janaab/supreme-court-speech](https://huggingface.co/janaab/supreme-court-speech) dataset.
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  It achieves the following results on the evaluation set:
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- - eval_loss: 0.3354
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- - eval_wer_ortho: 11.0780
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- - eval_wer: 10.5653
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- - eval_runtime: 1059.0881
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- - eval_samples_per_second: 4.216
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- - eval_steps_per_second: 0.264
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- - epoch: 6.9337
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- - step: 2250
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  ## Model description
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@@ -50,15 +43,13 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-06
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
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- - gradient_accumulation_steps: 2
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- - total_train_batch_size: 32
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- - lr_scheduler_type: cosine_with_restarts
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- - lr_scheduler_warmup_steps: 50
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- - training_steps: 4000
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  - mixed_precision_training: Native AMP
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  ### Framework versions
@@ -66,4 +57,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.44.2
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  - Pytorch 2.4.0
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  - Datasets 2.21.0
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- - Tokenizers 0.19.1
 
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  model-index:
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  - name: whisper-small-sc
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  results: []
 
 
 
 
 
 
 
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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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  # whisper-small-sc
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - eval_loss: 0.2616
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+ - eval_wer_ortho: 11.1994
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+ - eval_wer: 10.7122
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+ - eval_runtime: 1028.1037
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+ - eval_samples_per_second: 4.343
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+ - eval_steps_per_second: 0.136
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+ - epoch: 4.6012
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+ - step: 750
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-06
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+ - train_batch_size: 64
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+ - eval_batch_size: 32
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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: 250
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+ - training_steps: 2500
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  - mixed_precision_training: Native AMP
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  ### Framework versions
 
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  - Transformers 4.44.2
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  - Pytorch 2.4.0
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  - Datasets 2.21.0
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+ - Tokenizers 0.19.1
config.json CHANGED
@@ -19,7 +19,7 @@
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  "decoder_layerdrop": 0.0,
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  "decoder_layers": 12,
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- "dropout": 0.0,
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  "encoder_attention_heads": 12,
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  "encoder_ffn_dim": 3072,
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  "encoder_layerdrop": 0.0,
 
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  "decoder_layerdrop": 0.0,
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  "decoder_layers": 12,
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  "decoder_start_token_id": 50258,
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+ "dropout": 0.1,
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  "encoder_attention_heads": 12,
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  "encoder_layerdrop": 0.0,
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