End of training

README.md

@@ -5,9 +5,24 @@ tags:
 - generated_from_trainer
 datasets:
 - PolyAI/minds14
+metrics:
+- wer
 model-index:
 - name: whisper-tiny-en
-  results: []
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: PolyAI/minds14
+      type: PolyAI/minds14
+      config: en-US
+      split: train
+      args: en-US
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.40703517587939697
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,6 +31,10 @@ should probably proofread and complete it, then remove this comment. -->
 # whisper-tiny-en
 
 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9685
+- Wer Ortho: 40.1048
+- Wer: 0.4070
 
 ## Model description
 
@@ -35,16 +54,20 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 16
+- train_batch_size: 32
 - eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: constant_with_warmup
 - lr_scheduler_warmup_steps: 50
-- training_steps: 100
+- training_steps: 1000
 
 ### Training results
 
+| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
+| 0.0006        | 31.25 | 500  | 0.8965          | 38.4010   | 0.3932 |
+| 0.0002        | 62.5  | 1000 | 0.9685          | 40.1048   | 0.4070 |
 
 
 ### Framework versions

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:0ba47670dd6f74cceb2a12251784bca79954d4da0c3db1679341981e6892a265
 size 151099494