End of training

README.md

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+---
+base_model: openai/whisper-large-v3
+datasets:
+- Gabi00/english-mistakes
+language:
+- eng
+library_name: peft
+license: apache-2.0
+metrics:
+- wer
+tags:
+- generated_from_trainer
+model-index:
+- name: Whisper Small Eng - Gabriel Mora
+  results:
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: English-mistakes
+      type: Gabi00/english-mistakes
+      config: default
+      split: validation
+      args: 'config: eng, split: test'
+    metrics:
+    - type: wer
+      value: 12.326814527624153
+      name: Wer
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# Whisper Small Eng - Gabriel Mora
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the English-mistakes dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3590
+- Wer: 12.3268
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 50
+- training_steps: 100000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.9094        | 0.1270 | 500  | 0.6347          | 24.3686 |
+| 0.5517        | 0.2541 | 1000 | 0.4835          | 18.0769 |
+| 0.5364        | 0.3811 | 1500 | 0.4330          | 15.1149 |
+| 0.5503        | 0.5081 | 2000 | 0.4113          | 13.6524 |
+| 0.6521        | 0.6352 | 2500 | 0.3987          | 13.5897 |
+| 0.6044        | 0.7622 | 3000 | 0.3912          | 13.0538 |
+| 0.5487        | 0.8892 | 3500 | 0.3835          | 12.6119 |
+| 0.5297        | 1.0163 | 4000 | 0.3791          | 12.4408 |
+| 0.46          | 1.1433 | 4500 | 0.3751          | 12.3525 |
+| 0.4947        | 1.2703 | 5000 | 0.3721          | 12.1415 |
+| 0.524         | 1.3974 | 5500 | 0.3682          | 13.0139 |
+| 0.4743        | 1.5244 | 6000 | 0.3649          | 13.3388 |
+| 0.5338        | 1.6514 | 6500 | 0.3621          | 12.9397 |
+| 0.5162        | 1.7785 | 7000 | 0.3597          | 13.3246 |
+| 0.5004        | 1.9055 | 7500 | 0.3590          | 12.3268 |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.42.4
+- Pytorch 2.1.0+cu118
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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