End of training

README.md

@@ -9,9 +9,22 @@ tags:
 - generated_from_trainer
 datasets:
 - Chinese_english
+metrics:
+- wer
 model-index:
 - name: Whisper tiny Chinese
-  results: []
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Chinese English
+      type: Chinese_english
+      args: 'config: default, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 16.282764098490865
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -21,13 +34,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Chinese English dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.3483
-- eval_wer: 15.8380
-- eval_runtime: 183.8429
-- eval_samples_per_second: 3.421
-- eval_steps_per_second: 3.421
-- epoch: 0.6667
-- step: 200
+- Loss: 0.3662
+- Wer: 16.2828
 
 ## Model description
 
@@ -55,6 +63,19 @@ The following hyperparameters were used during training:
 - lr_scheduler_warmup_steps: 500
 - training_steps: 1500
 
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.3967        | 0.6667 | 200  | 0.4181          | 20.5401 |
+| 0.2613        | 1.3333 | 400  | 0.3772          | 18.1573 |
+| 0.2237        | 2.0    | 600  | 0.3532          | 15.9333 |
+| 0.0728        | 2.6667 | 800  | 0.3657          | 16.3622 |
+| 0.0357        | 3.3333 | 1000 | 0.3564          | 17.3630 |
+| 0.0108        | 4.0    | 1200 | 0.3544          | 16.1716 |
+| 0.0039        | 4.6667 | 1400 | 0.3662          | 16.2828 |
+
+
 ### Framework versions
 
 - Transformers 4.49.0

model.safetensors

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runs/Apr17_22-06-23_151d3cb3111a/events.out.tfevents.1744927607.151d3cb3111a.220.2

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