End of training

README.md

@@ -19,8 +19,8 @@ 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 HAT ASR Aligned dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1959
-- Cer: 12.2188
+- Loss: 0.1402
+- Cer: 8.5108
 
 ## Model description
 
@@ -39,40 +39,30 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
+- learning_rate: 0.0001
 - train_batch_size: 64
 - eval_batch_size: 32
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 976
-- training_steps: 9760
+- lr_scheduler_warmup_steps: 488
+- training_steps: 4880
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch   | Step | Validation Loss | Cer     |
-|:-------------:|:-------:|:----:|:---------------:|:-------:|
-| 1.189         | 0.9980  | 488  | 1.2025          | 50.1503 |
-| 0.3904        | 1.9959  | 976  | 0.4830          | 26.8916 |
-| 0.2027        | 2.9939  | 1464 | 0.3017          | 17.2273 |
-| 0.1241        | 3.9918  | 1952 | 0.2566          | 15.3859 |
-| 0.0837        | 4.9898  | 2440 | 0.2299          | 14.5098 |
-| 0.0558        | 5.9877  | 2928 | 0.2175          | 13.6302 |
-| 0.0365        | 6.9857  | 3416 | 0.2119          | 13.6151 |
-| 0.0266        | 7.9836  | 3904 | 0.2052          | 13.6059 |
-| 0.0197        | 8.9816  | 4392 | 0.1990          | 11.9877 |
-| 0.0131        | 9.9796  | 4880 | 0.1982          | 12.7887 |
-| 0.0082        | 10.9775 | 5368 | 0.1987          | 12.5864 |
-| 0.006         | 11.9755 | 5856 | 0.1985          | 13.6336 |
-| 0.0046        | 12.9734 | 6344 | 0.1971          | 13.0037 |
-| 0.0035        | 13.9714 | 6832 | 0.1945          | 12.7390 |
-| 0.0034        | 14.9693 | 7320 | 0.1966          | 12.7135 |
-| 0.0026        | 15.9673 | 7808 | 0.1954          | 12.6477 |
-| 0.0022        | 16.9652 | 8296 | 0.1958          | 12.5922 |
-| 0.0021        | 17.9632 | 8784 | 0.1957          | 11.5970 |
-| 0.0019        | 18.9611 | 9272 | 0.1959          | 12.0061 |
-| 0.0018        | 19.9591 | 9760 | 0.1959          | 12.2188 |
+| Training Loss | Epoch  | Step | Validation Loss | Cer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.2096        | 0.9980 | 488  | 0.3010          | 27.0939 |
+| 0.1035        | 1.9959 | 976  | 0.2198          | 18.4063 |
+| 0.0491        | 2.9939 | 1464 | 0.1966          | 12.8661 |
+| 0.0261        | 3.9918 | 1952 | 0.1766          | 14.3364 |
+| 0.0117        | 4.9898 | 2440 | 0.1576          | 10.6133 |
+| 0.0045        | 5.9877 | 2928 | 0.1425          | 11.8732 |
+| 0.0014        | 6.9857 | 3416 | 0.1471          | 9.7591  |
+| 0.0006        | 7.9836 | 3904 | 0.1413          | 8.8356  |
+| 0.0005        | 8.9816 | 4392 | 0.1413          | 8.6079  |
+| 0.0003        | 9.9796 | 4880 | 0.1402          | 8.5108  |
 
 
 ### Framework versions