End of training

README.md

@@ -0,0 +1,87 @@
+---
+language:
+- es
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- generated_from_trainer
+datasets:
+- facebook/multilingual_librispeech
+metrics:
+- wer
+model-index:
+- name: Whisper Medium es - Dash Guitar
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: facebook/multilingual_librispeech
+      type: facebook/multilingual_librispeech
+      config: spanish
+      split: test
+      args: spanish
+    metrics:
+    - name: Wer
+      type: wer
+      value: 7.085875706214689
+---
+
+<!-- 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 Medium es - Dash Guitar
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the facebook/multilingual_librispeech dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1535
+- Wer Ortho: 7.0848
+- Wer: 7.0859
+
+## 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: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: constant_with_warmup
+- lr_scheduler_warmup_steps: 50
+- training_steps: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
+| 0.3349        | 0.02  | 500  | 0.1782          | 8.1526    | 8.1571 |
+| 0.309         | 0.04  | 1000 | 0.1702          | 7.5899    | 7.5921 |
+| 0.2814        | 0.05  | 1500 | 0.1680          | 8.0103    | 8.0124 |
+| 0.3067        | 0.07  | 2000 | 0.1665          | 8.1007    | 8.1028 |
+| 0.3223        | 0.09  | 2500 | 0.1751          | 9.2272    | 9.2294 |
+| 0.2696        | 0.11  | 3000 | 0.1583          | 7.2374    | 7.2395 |
+| 0.3203        | 0.13  | 3500 | 0.1542          | 6.9560    | 6.9559 |
+| 0.2655        | 0.14  | 4000 | 0.1535          | 7.0848    | 7.0859 |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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