Wiam
/

wav2vec2-base-finetuned-ravdess

@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.8659
-- Accuracy: 0.3646
 ## Model description
@@ -46,17 +46,62 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 5
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 1.0   | 9    | 2.0626          | 0.2361   |
-| 2.0699        | 2.0   | 18   | 2.0309          | 0.2292   |
-| 2.0333        | 3.0   | 27   | 1.9581          | 0.3229   |
-| 1.9763        | 4.0   | 36   | 1.8941          | 0.3507   |
-| 1.9042        | 5.0   | 45   | 1.8659          | 0.3646   |
 ### Framework versions

 This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.9291
+- Accuracy: 0.7431
 ## Model description
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 50
 ### Training results
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 9    | 1.8542          | 0.375    |
+| 1.8624        | 2.0   | 18   | 1.7931          | 0.4410   |
+| 1.8211        | 3.0   | 27   | 1.7181          | 0.4479   |
+| 1.7355        | 4.0   | 36   | 1.6184          | 0.4861   |
+| 1.6208        | 5.0   | 45   | 1.5383          | 0.4965   |
+| 1.4999        | 6.0   | 54   | 1.4630          | 0.5069   |
+| 1.4016        | 7.0   | 63   | 1.4161          | 0.5278   |
+| 1.3028        | 8.0   | 72   | 1.3513          | 0.5312   |
+| 1.2202        | 9.0   | 81   | 1.3359          | 0.5625   |
+| 1.1506        | 10.0  | 90   | 1.3518          | 0.5625   |
+| 1.1506        | 11.0  | 99   | 1.2043          | 0.6076   |
+| 1.0749        | 12.0  | 108  | 1.2926          | 0.5833   |
+| 0.993         | 13.0  | 117  | 1.1970          | 0.6181   |
+| 0.8961        | 14.0  | 126  | 1.1593          | 0.6285   |
+| 0.8062        | 15.0  | 135  | 1.1184          | 0.6424   |
+| 0.7547        | 16.0  | 144  | 1.1318          | 0.6285   |
+| 0.7192        | 17.0  | 153  | 1.0872          | 0.6493   |
+| 0.65          | 18.0  | 162  | 1.0737          | 0.6528   |
+| 0.6142        | 19.0  | 171  | 1.0677          | 0.6597   |
+| 0.5845        | 20.0  | 180  | 1.0220          | 0.6806   |
+| 0.5845        | 21.0  | 189  | 0.9968          | 0.6840   |
+| 0.5217        | 22.0  | 198  | 0.9864          | 0.6840   |
+| 0.4798        | 23.0  | 207  | 0.9708          | 0.6840   |
+| 0.4501        | 24.0  | 216  | 1.0981          | 0.6632   |
+| 0.4339        | 25.0  | 225  | 1.0536          | 0.6806   |
+| 0.4274        | 26.0  | 234  | 0.9387          | 0.6979   |
+| 0.3742        | 27.0  | 243  | 0.9879          | 0.6979   |
+| 0.3747        | 28.0  | 252  | 0.9773          | 0.6979   |
+| 0.3389        | 29.0  | 261  | 0.9257          | 0.7361   |
+| 0.3213        | 30.0  | 270  | 0.9292          | 0.7049   |
+| 0.3213        | 31.0  | 279  | 0.9555          | 0.7153   |
+| 0.3007        | 32.0  | 288  | 0.9733          | 0.7083   |
+| 0.2681        | 33.0  | 297  | 1.0336          | 0.6979   |
+| 0.2576        | 34.0  | 306  | 1.0443          | 0.6875   |
+| 0.2561        | 35.0  | 315  | 0.9261          | 0.7292   |
+| 0.2575        | 36.0  | 324  | 1.0833          | 0.6771   |
+| 0.2483        | 37.0  | 333  | 0.9775          | 0.7083   |
+| 0.2108        | 38.0  | 342  | 0.8911          | 0.7326   |
+| 0.218         | 39.0  | 351  | 1.0301          | 0.6840   |
+| 0.1927        | 40.0  | 360  | 0.9935          | 0.7014   |
+| 0.1927        | 41.0  | 369  | 0.9619          | 0.7292   |
+| 0.1945        | 42.0  | 378  | 1.0197          | 0.6944   |
+| 0.1926        | 43.0  | 387  | 0.9291          | 0.7431   |
+| 0.1799        | 44.0  | 396  | 1.0348          | 0.6875   |
+| 0.1768        | 45.0  | 405  | 0.9899          | 0.7153   |
+| 0.1728        | 46.0  | 414  | 1.0284          | 0.7049   |
+| 0.1713        | 47.0  | 423  | 1.0527          | 0.7049   |
+| 0.1638        | 48.0  | 432  | 1.0001          | 0.7083   |
+| 0.159         | 49.0  | 441  | 0.9931          | 0.7153   |
+| 0.1637        | 50.0  | 450  | 1.0015          | 0.7118   |
 ### Framework versions