End of training

README.md

@@ -0,0 +1,87 @@
+---
+language:
+- sr
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- generated_from_trainer
+datasets:
+- espnet/yodas
+metrics:
+- wer
+model-index:
+- name: Whisper Small Sr Yodas
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Yodas
+      type: espnet/yodas
+      config: sr
+      split: test
+      args: sr
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.24497708847373986
+---
+
+<!-- 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 Sr Yodas
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Yodas dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2688
+- Wer Ortho: 0.3334
+- Wer: 0.2450
+
+## 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: 16
+- 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: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
+| 1.0469        | 0.24  | 500  | 0.4020          | 0.5071    | 0.4270 |
+| 0.9924        | 0.49  | 1000 | 0.3401          | 0.4082    | 0.3183 |
+| 0.865         | 0.73  | 1500 | 0.3047          | 0.3644    | 0.2776 |
+| 0.8443        | 0.98  | 2000 | 0.2893          | 0.3623    | 0.2735 |
+| 0.7377        | 1.22  | 2500 | 0.2817          | 0.3472    | 0.2591 |
+| 0.6851        | 1.46  | 3000 | 0.2728          | 0.3348    | 0.2466 |
+| 0.7286        | 1.71  | 3500 | 0.2702          | 0.3325    | 0.2444 |
+| 0.7215        | 1.95  | 4000 | 0.2688          | 0.3334    | 0.2450 |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.0.1+cu117
+- Datasets 2.18.0
+- Tokenizers 0.15.1

generation_config.json

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+}

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