Model save

README.md

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+---
+license: apache-2.0
+base_model: openai/whisper-large-v3
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_13_0
+metrics:
+- wer
+model-index:
+- name: openai/whisper-large-v3
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_13_0
+      type: common_voice_13_0
+      config: es
+      split: test
+      args: es
+    metrics:
+    - name: Wer
+      type: wer
+      value: 4.9295277686894154
+---
+
+<!-- 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. -->
+
+# openai/whisper-large-v3
+
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the common_voice_13_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3245
+- Wer: 4.9295
+
+## 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: 32
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 20000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Wer    |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|
+| 0.058         | 2.04  | 1000  | 0.1540          | 4.6851 |
+| 0.0124        | 4.07  | 2000  | 0.1829          | 4.6787 |
+| 0.0052        | 6.11  | 3000  | 0.2190          | 4.8096 |
+| 0.0024        | 8.15  | 4000  | 0.2289          | 4.8776 |
+| 0.0024        | 10.18 | 5000  | 0.2341          | 4.8923 |
+| 0.0015        | 12.22 | 6000  | 0.2459          | 4.9340 |
+| 0.0021        | 14.26 | 7000  | 0.2558          | 4.9276 |
+| 0.0011        | 16.29 | 8000  | 0.2540          | 5.1015 |
+| 0.0013        | 18.33 | 9000  | 0.2611          | 5.1855 |
+| 0.0005        | 20.37 | 10000 | 0.2720          | 4.9379 |
+| 0.0028        | 22.4  | 11000 | 0.2614          | 5.0110 |
+| 0.0004        | 24.44 | 12000 | 0.2652          | 4.9898 |
+| 0.0004        | 26.48 | 13000 | 0.2850          | 4.9776 |
+| 0.0006        | 28.51 | 14000 | 0.2736          | 4.9732 |
+| 0.0002        | 30.55 | 15000 | 0.2944          | 5.1566 |
+| 0.0002        | 32.59 | 16000 | 0.2949          | 5.0007 |
+| 0.0001        | 34.62 | 17000 | 0.3094          | 4.9552 |
+| 0.0           | 36.66 | 18000 | 0.3185          | 4.9622 |
+| 0.0           | 38.7  | 19000 | 0.3229          | 4.9462 |
+| 0.0           | 40.73 | 20000 | 0.3245          | 4.9295 |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.2.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

generation_config.json

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+      0
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+    [
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+  "decoder_start_token_id": 50258,
+  "eos_token_id": 50257,
+  "forced_decoder_ids": [
+    [
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+    [
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+  "max_length": 448,
+  "no_timestamps_token_id": 50364,
+  "pad_token_id": 50257,
+  "prev_sot_token_id": 50362,
+  "return_timestamps": false,
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+  "transformers_version": "4.37.2"
+}

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