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  1. README.md +72 -0
  2. added_tokens.json +6 -0
  3. all_results.json +14 -0
  4. checkpoint-14000/added_tokens.json +6 -0
  5. checkpoint-14000/config.json +117 -0
  6. checkpoint-14000/optimizer.pt +3 -0
  7. checkpoint-14000/preprocessor_config.json +10 -0
  8. checkpoint-14000/pytorch_model.bin +3 -0
  9. checkpoint-14000/rng_state_0.pth +3 -0
  10. checkpoint-14000/rng_state_1.pth +3 -0
  11. checkpoint-14000/rng_state_2.pth +3 -0
  12. checkpoint-14000/rng_state_3.pth +3 -0
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  16. checkpoint-14000/trainer_state.json +502 -0
  17. checkpoint-14000/training_args.bin +3 -0
  18. checkpoint-14000/vocab.json +3078 -0
  19. checkpoint-4000/added_tokens.json +6 -0
  20. checkpoint-4000/config.json +117 -0
  21. checkpoint-4000/optimizer.pt +3 -0
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  26. checkpoint-4000/rng_state_2.pth +3 -0
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  31. checkpoint-4000/trainer_state.json +157 -0
  32. checkpoint-4000/training_args.bin +3 -0
  33. checkpoint-4000/vocab.json +3078 -0
  34. config.json +117 -0
  35. eval_results.json +9 -0
  36. preprocessor_config.json +10 -0
  37. pytorch_model.bin +3 -0
  38. special_tokens_map.json +10 -0
  39. tokenizer_config.json +56 -0
  40. train_results.json +8 -0
  41. trainer_state.json +511 -0
  42. training_args.bin +3 -0
  43. vocab.json +3078 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-large-xlsr-53
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+ tags:
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+ - automatic-speech-recognition
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+ - ./sample_speech.py
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+ - generated_from_trainer
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+ model-index:
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+ - name: zh-xlsr3
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+ results: []
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+ ---
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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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+
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+ # zh-xlsr3
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.9402
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+ - Cer: 0.4156
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0003
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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+ - total_eval_batch_size: 16
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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: 1000
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+ - num_epochs: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Cer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 2.9893 | 6.08 | 2000 | 2.4704 | 0.5279 |
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+ | 1.9656 | 12.16 | 4000 | 1.9401 | 0.4185 |
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+ | 1.4552 | 18.24 | 6000 | 1.9569 | 0.4053 |
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+ | 1.1015 | 24.32 | 8000 | 2.1087 | 0.3982 |
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+ | 0.8761 | 30.4 | 10000 | 2.2972 | 0.4272 |
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+ | 0.6962 | 36.47 | 12000 | 2.4389 | 0.4153 |
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+ | 0.5562 | 42.55 | 14000 | 2.5137 | 0.4164 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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+ "train_loss": 2.5468389271327427,
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+ "train_samples": 21048,
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+ "train_samples_per_second": 111.714,
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+ "train_steps_per_second": 1.746
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+ }
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