End of training

README.md

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+---
+base_model: distil-whisper/distil-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: 18.4360567877302
+      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: 0.6839
+- Wer: 18.4361
+
+## 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: 28
+- eval_batch_size: 28
+- 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     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 1.5189        | 0.4444 | 500  | 1.1913          | 25.9108 |
+| 1.1727        | 0.8889 | 1000 | 0.9531          | 24.5396 |
+| 1.1341        | 1.3333 | 1500 | 0.8688          | 22.2761 |
+| 1.0152        | 1.7778 | 2000 | 0.8174          | 20.8792 |
+| 1.0589        | 2.2222 | 2500 | 0.7855          | 20.7595 |
+| 0.9793        | 2.6667 | 3000 | 0.7611          | 22.2846 |
+| 0.9594        | 3.1111 | 3500 | 0.7442          | 20.3860 |
+| 1.0031        | 3.5556 | 4000 | 0.7303          | 18.5045 |
+| 0.9525        | 4.0    | 4500 | 0.7199          | 18.1054 |
+| 0.8729        | 4.4444 | 5000 | 0.7105          | 19.3170 |
+| 1.0031        | 4.8889 | 5500 | 0.7028          | 19.7446 |
+| 0.9273        | 5.3333 | 6000 | 0.6966          | 19.7189 |
+| 0.9174        | 5.7778 | 6500 | 0.6896          | 18.4475 |
+| 0.8842        | 6.2222 | 7000 | 0.6839          | 18.4361 |
+
+
+### 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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