Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: openai/whisper-large
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: whisper-small-obs-dataset
+  results: []
+---
+
+<!-- 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-obs-dataset
+
+This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3014
+- Wer: 87.4401
+
+## 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: 80
+- training_steps: 200
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer      |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 1.1319        | 1.0417 | 100  | 1.3716          | 119.4252 |
+| 0.8298        | 2.0833 | 200  | 1.3014          | 87.4401  |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu124
+- Datasets 2.21.0
+- Tokenizers 0.19.1

generation_config.json

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+  "decoder_start_token_id": 50258,
+  "eos_token_id": 50257,
+  "is_multilingual": true,
+  "lang_to_id": {
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+  "task": "transcribe",
+  "task_to_id": {
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+    "translate": 50358
+  },
+  "transformers_version": "4.44.2"
+}

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