End of training

README.md

@@ -0,0 +1,112 @@
+---
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- generated_from_trainer
+datasets:
+- mozilla-foundation/fsc-audio-dataset
+metrics:
+- wer
+model-index:
+- name: Personalized Whisper Small - Wei Fang
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: fsc-audio-dataset
+      type: mozilla-foundation/fsc-audio-dataset
+    metrics:
+    - name: Wer
+      type: wer
+      value: 8.372290692732681
+---
+
+<!-- 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. -->
+
+# Personalized Whisper Small - Wei Fang
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the fsc-audio-dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2946
+- Wer: 8.3723
+
+## 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: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 4000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.9814        | 0.32  | 100  | 0.8164          | 13.2172 |
+| 0.3013        | 0.64  | 200  | 0.2578          | 11.7722 |
+| 0.2074        | 0.96  | 300  | 0.2192          | 10.4972 |
+| 0.1429        | 1.28  | 400  | 0.2245          | 11.0072 |
+| 0.1565        | 1.6   | 500  | 0.2102          | 10.6247 |
+| 0.1554        | 1.92  | 600  | 0.2137          | 11.2197 |
+| 0.0684        | 2.24  | 700  | 0.2139          | 8.8823  |
+| 0.0717        | 2.56  | 800  | 0.2142          | 9.6898  |
+| 0.0795        | 2.88  | 900  | 0.2128          | 9.2223  |
+| 0.0329        | 3.21  | 1000 | 0.2341          | 9.3073  |
+| 0.03          | 3.53  | 1100 | 0.2324          | 8.9673  |
+| 0.0319        | 3.85  | 1200 | 0.2365          | 9.0948  |
+| 0.0137        | 4.17  | 1300 | 0.2403          | 9.0523  |
+| 0.0145        | 4.49  | 1400 | 0.2470          | 8.3723  |
+| 0.0145        | 4.81  | 1500 | 0.2596          | 9.4348  |
+| 0.0067        | 5.13  | 1600 | 0.2544          | 8.9248  |
+| 0.0088        | 5.45  | 1700 | 0.2553          | 8.4573  |
+| 0.0065        | 5.77  | 1800 | 0.2729          | 8.8823  |
+| 0.0018        | 6.09  | 1900 | 0.2680          | 8.7973  |
+| 0.0023        | 6.41  | 2000 | 0.2710          | 9.0948  |
+| 0.0018        | 6.73  | 2100 | 0.2762          | 8.8398  |
+| 0.002         | 7.05  | 2200 | 0.2717          | 8.5848  |
+| 0.0011        | 7.37  | 2300 | 0.2784          | 8.5423  |
+| 0.0012        | 7.69  | 2400 | 0.2797          | 8.4573  |
+| 0.0011        | 8.01  | 2500 | 0.2782          | 8.3723  |
+| 0.0007        | 8.33  | 2600 | 0.2838          | 8.1598  |
+| 0.0007        | 8.65  | 2700 | 0.2826          | 8.2448  |
+| 0.0013        | 8.97  | 2800 | 0.2835          | 8.4148  |
+| 0.0006        | 9.29  | 2900 | 0.2913          | 8.2448  |
+| 0.0006        | 9.62  | 3000 | 0.2906          | 8.4148  |
+| 0.001         | 9.94  | 3100 | 0.2886          | 8.6273  |
+| 0.0005        | 10.26 | 3200 | 0.2890          | 8.3723  |
+| 0.0005        | 10.58 | 3300 | 0.2905          | 8.3723  |
+| 0.0005        | 10.9  | 3400 | 0.2917          | 8.4573  |
+| 0.0008        | 11.22 | 3500 | 0.2927          | 8.3723  |
+| 0.0019        | 11.54 | 3600 | 0.2932          | 8.3723  |
+| 0.0004        | 11.86 | 3700 | 0.2939          | 8.3723  |
+| 0.0004        | 12.18 | 3800 | 0.2941          | 8.3723  |
+| 0.0005        | 12.5  | 3900 | 0.2944          | 8.3723  |
+| 0.0005        | 12.82 | 4000 | 0.2946          | 8.3723  |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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