End of training

README.md

@@ -0,0 +1,90 @@
+---
+language:
+- en
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- generated_from_trainer
+datasets:
+- librispeech_asr
+metrics:
+- wer
+model-index:
+- name: Whisper-Small En-10m
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: librispeech
+      type: librispeech_asr
+      config: default
+      split: None
+      args: 'config: en, split: test-clean'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 3.7424325811777654
+---
+
+<!-- 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 En-10m
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the librispeech dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3635
+- Wer: 3.7424
+
+## 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: 5e-07
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 300
+- training_steps: 1000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch    | Step | Validation Loss | Wer    |
+|:-------------:|:--------:|:----:|:---------------:|:------:|
+| 0.482         | 33.3333  | 100  | 0.7436          | 3.4183 |
+| 0.2402        | 66.6667  | 200  | 0.5833          | 3.4448 |
+| 0.0135        | 100.0    | 300  | 0.3881          | 3.5834 |
+| 0.0029        | 133.3333 | 400  | 0.3731          | 3.6324 |
+| 0.0019        | 166.6667 | 500  | 0.3685          | 3.6568 |
+| 0.0014        | 200.0    | 600  | 0.3663          | 3.6854 |
+| 0.0012        | 233.3333 | 700  | 0.3649          | 3.7098 |
+| 0.0011        | 266.6667 | 800  | 0.3641          | 3.7241 |
+| 0.001         | 300.0    | 900  | 0.3637          | 3.7465 |
+| 0.001         | 333.3333 | 1000 | 0.3635          | 3.7424 |
+
+
+### Framework versions
+
+- Transformers 4.41.0.dev0
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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+}

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