End of training

README.md

@@ -0,0 +1,101 @@
+---
+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: 18.233650721249788
+      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: 0.6550
+- Wer: 18.2337
+
+## 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     |
+|:-------------:|:------:|:-----:|:---------------:|:-------:|
+| 1.5085        | 0.4444 | 500   | 1.1844          | 25.9507 |
+| 1.1717        | 0.8889 | 1000  | 0.9522          | 25.2751 |
+| 1.1302        | 1.3333 | 1500  | 0.8634          | 22.0879 |
+| 1.0094        | 1.7778 | 2000  | 0.8098          | 21.0103 |
+| 1.0509        | 2.2222 | 2500  | 0.7784          | 23.2054 |
+| 0.9722        | 2.6667 | 3000  | 0.7555          | 21.5206 |
+| 0.9562        | 3.1111 | 3500  | 0.7401          | 21.0075 |
+| 0.9995        | 3.5556 | 4000  | 0.7269          | 19.8985 |
+| 0.9497        | 4.0    | 4500  | 0.7170          | 19.3626 |
+| 0.8703        | 4.4444 | 5000  | 0.7078          | 19.4652 |
+| 1.0015        | 4.8889 | 5500  | 0.7004          | 20.1608 |
+| 0.9248        | 5.3333 | 6000  | 0.6947          | 17.7034 |
+| 0.9163        | 5.7778 | 6500  | 0.6880          | 17.4953 |
+| 0.8833        | 6.2222 | 7000  | 0.6823          | 17.4668 |
+| 0.9051        | 6.6667 | 7500  | 0.6770          | 17.4554 |
+| 0.8882        | 7.1111 | 8000  | 0.6730          | 17.3613 |
+| 0.8879        | 7.5556 | 8500  | 0.6684          | 18.3220 |
+| 0.8396        | 8.0    | 9000  | 0.6647          | 18.2165 |
+| 0.9282        | 8.4444 | 9500  | 0.6616          | 18.4646 |
+| 0.8581        | 8.8889 | 10000 | 0.6578          | 18.1538 |
+| 0.8938        | 9.3333 | 10500 | 0.6550          | 18.2337 |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.42.3
+- Pytorch 2.1.0+cu118
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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