End of training

README.md

@@ -16,13 +16,13 @@ model-index:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: 'This is a dataset constructed from two datasets: ATCO2-ASR and ATCOSIM.'
+      name: 'This is a dataset constructed from two datasets: ATCOSIM.'
       type: Jzuluaga/atcosim_corpus
-      args: 'config: en, split: test small split [3000]'
+      args: 'config: en, split: test small split [full]'
     metrics:
     - name: Wer
       type: wer
-      value: 8.947972793922798
+      value: 1.4177192827488738
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # Whisper small - Whisper with atcosim
 
-This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the This is a dataset constructed from two datasets: ATCO2-ASR and ATCOSIM. dataset.
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the This is a dataset constructed from two datasets: ATCOSIM. dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2504
-- Wer: 8.9480
+- Loss: 0.0385
+- Wer: 1.4177
 
 ## Model description
 
@@ -64,23 +64,23 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Wer     |
-|:-------------:|:------:|:----:|:---------------:|:-------:|
-| 0.0569        | 0.5319 | 100  | 0.3078          | 11.7922 |
-| 0.0307        | 1.0638 | 200  | 0.2728          | 10.8515 |
-| 0.0253        | 1.5957 | 300  | 0.2762          | 10.7190 |
-| 0.0066        | 2.1277 | 400  | 0.2551          | 9.0761  |
-| 0.0061        | 2.6596 | 500  | 0.2526          | 9.5795  |
-| 0.002         | 3.1915 | 600  | 0.2504          | 9.0010  |
-| 0.0019        | 3.7234 | 700  | 0.2561          | 9.2880  |
-| 0.0007        | 4.2553 | 800  | 0.2535          | 9.1026  |
-| 0.001         | 4.7872 | 900  | 0.2495          | 8.9259  |
-| 0.0003        | 5.3191 | 1000 | 0.2504          | 8.9480  |
+| Training Loss | Epoch  | Step | Validation Loss | Wer    |
+|:-------------:|:------:|:----:|:---------------:|:------:|
+| 0.0349        | 0.2092 | 100  | 0.0974          | 6.4040 |
+| 0.0493        | 0.4184 | 200  | 0.0664          | 3.2329 |
+| 0.0464        | 0.6276 | 300  | 0.0519          | 2.8708 |
+| 0.0394        | 0.8368 | 400  | 0.0474          | 2.3055 |
+| 0.0177        | 1.0460 | 500  | 0.0429          | 1.7004 |
+| 0.0054        | 1.2552 | 600  | 0.0416          | 1.5458 |
+| 0.0182        | 1.4644 | 700  | 0.0411          | 1.5193 |
+| 0.008         | 1.6736 | 800  | 0.0400          | 1.4663 |
+| 0.0055        | 1.8828 | 900  | 0.0387          | 1.4619 |
+| 0.0053        | 2.0921 | 1000 | 0.0385          | 1.4177 |
 
 
 ### Framework versions
 
 - Transformers 4.41.2
 - Pytorch 2.3.0+cu121
-- Datasets 2.19.2
+- Datasets 2.20.0
 - Tokenizers 0.19.1