End of training

README.md

@@ -11,19 +11,19 @@ datasets:
 metrics:
 - wer
 model-index:
-- name: Whisper Tiny En - FreeSound based captions test
+- name: Whisper Tiny En - FreeSound based captions
   results: []
 ---
 
 <!-- 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 Tiny En - FreeSound based captions test
+# Whisper Tiny En - FreeSound based captions
 
 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the FreeSound Audio dataset.
 It achieves the following results on the evaluation set:
-- Loss: 3.8548
-- Wer: 98.5500
+- Loss: 5.5085
+- Wer: 91.7867
 
 ## Model description
 
@@ -48,18 +48,21 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 10
-- training_steps: 100
+- lr_scheduler_warmup_steps: 500
+- training_steps: 7000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Wer      |
-|:-------------:|:------:|:----:|:---------------:|:--------:|
-| 5.2273        | 0.6098 | 25   | 4.9782          | 101.4246 |
-| 4.0984        | 1.2195 | 50   | 4.1433          | 100.8904 |
-| 3.8301        | 1.8293 | 75   | 3.9157          | 99.3132  |
-| 3.7081        | 2.4390 | 100  | 3.8548          | 98.5500  |
+| Training Loss | Epoch    | Step | Validation Loss | Wer     |
+|:-------------:|:--------:|:----:|:---------------:|:-------:|
+| 0.8757        | 24.3902  | 1000 | 4.1235          | 97.8963 |
+| 0.0518        | 48.7805  | 2000 | 4.8741          | 94.9280 |
+| 0.0234        | 73.1707  | 3000 | 5.1544          | 93.1124 |
+| 0.0148        | 97.5610  | 4000 | 5.3503          | 93.4294 |
+| 0.0141        | 121.9512 | 5000 | 5.4099          | 92.3631 |
+| 0.0112        | 146.3415 | 6000 | 5.4837          | 92.4496 |
+| 0.0104        | 170.7317 | 7000 | 5.5085          | 91.7867 |
 
 
 ### Framework versions