Model save

README.md

@@ -1,43 +1,25 @@
 ---
 library_name: transformers
-language:
-- eu
 license: apache-2.0
 base_model: openai/whisper-large-v3
 tags:
-- whisper-event
 - generated_from_trainer
-datasets:
-- mozilla-foundation/common_voice_17_0
 metrics:
 - wer
 model-index:
-- name: Whisper Large Basque
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: mozilla-foundation/common_voice_17_0 eu
-      type: mozilla-foundation/common_voice_17_0
-      config: eu
-      split: test
-      args: eu
-    metrics:
-    - name: Wer
-      type: wer
-      value: 7.215361500971087
+- name: openai/whisper-large-v3
+  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 Large Basque
+# openai/whisper-large-v3
 
-This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the mozilla-foundation/common_voice_17_0 eu dataset.
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1259
-- Wer: 7.2154
+- Loss: 0.1834
+- Wer: 8.6426
 
 ## Model description
 
@@ -62,37 +44,39 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 500
+- lr_scheduler_warmup_steps: 1000
 - training_steps: 10000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Wer     |
-|:-------------:|:------:|:----:|:---------------:|:-------:|
-| 0.2208        | 0.05   | 500  | 0.2592          | 20.6915 |
-| 0.1489        | 0.1    | 1000 | 0.1971          | 14.6827 |
-| 0.1973        | 0.15   | 1500 | 0.1747          | 12.3777 |
-| 0.1353        | 1.0296 | 2000 | 0.1527          | 10.7195 |
-| 0.1065        | 1.0796 | 2500 | 0.1456          | 9.8694  |
-| 0.106         | 1.1296 | 3000 | 0.1362          | 9.0925  |
-| 0.0718        | 2.0092 | 3500 | 0.1326          | 8.5428  |
-| 0.0683        | 2.0592 | 4000 | 0.1343          | 8.4851  |
-| 0.0482        | 2.1092 | 4500 | 0.1336          | 8.1049  |
-| 0.0548        | 2.1592 | 5000 | 0.1316          | 7.9244  |
-| 0.0282        | 3.0388 | 5500 | 0.1391          | 7.8182  |
-| 0.025         | 3.0888 | 6000 | 0.1425          | 7.9409  |
-| 0.0274        | 3.1388 | 6500 | 0.1391          | 7.7311  |
-| 0.0155        | 4.0184 | 7000 | 0.1492          | 7.6972  |
-| 0.0189        | 4.0684 | 7500 | 0.1517          | 7.6569  |
-| 0.0139        | 4.1184 | 8000 | 0.1539          | 7.6267  |
-| 0.0141        | 4.1684 | 8500 | 0.1550          | 7.5424  |
-| 0.0368        | 5.048  | 9000 | 0.1259          | 7.2154  |
+| Training Loss | Epoch | Step  | Validation Loss | Wer     |
+|:-------------:|:-----:|:-----:|:---------------:|:-------:|
+| 0.2854        | 0.05  | 500   | 0.3763          | 24.9836 |
+| 0.1425        | 0.1   | 1000  | 0.3326          | 19.8654 |
+| 0.2196        | 0.15  | 1500  | 0.2802          | 16.2475 |
+| 0.2338        | 0.2   | 2000  | 0.2536          | 14.6116 |
+| 0.1383        | 0.25  | 2500  | 0.2451          | 12.8961 |
+| 0.0848        | 0.3   | 3000  | 0.2280          | 12.2464 |
+| 0.0854        | 0.35  | 3500  | 0.2152          | 11.4144 |
+| 0.1304        | 0.4   | 4000  | 0.2097          | 11.1433 |
+| 0.1328        | 0.45  | 4500  | 0.2055          | 10.6011 |
+| 0.0737        | 0.5   | 5000  | 0.2079          | 10.5357 |
+| 0.0804        | 0.55  | 5500  | 0.2133          | 10.1150 |
+| 0.0964        | 0.6   | 6000  | 0.1988          | 9.4606  |
+| 0.0811        | 0.65  | 6500  | 0.2019          | 9.4933  |
+| 0.0677        | 0.7   | 7000  | 0.1916          | 8.9231  |
+| 0.1114        | 0.75  | 7500  | 0.2029          | 9.3250  |
+| 0.1142        | 0.8   | 8000  | 0.1895          | 8.9978  |
+| 0.0466        | 0.85  | 8500  | 0.1936          | 8.8576  |
+| 0.0664        | 0.9   | 9000  | 0.1876          | 8.9698  |
+| 0.0759        | 0.95  | 9500  | 0.1827          | 8.8202  |
+| 0.0555        | 1.0   | 10000 | 0.1834          | 8.6426  |
 
 
 ### Framework versions
 
-- Transformers 4.46.0.dev0
-- Pytorch 2.4.1+cu121
-- Datasets 3.0.2.dev0
-- Tokenizers 0.20.0
+- Transformers 4.49.0.dev0
+- Pytorch 2.6.0+cu124
+- Datasets 3.2.1.dev0
+- Tokenizers 0.21.0

generation_config.json

@@ -261,5 +261,5 @@
     "transcribe": 50360,
     "translate": 50359
   },
-  "transformers_version": "4.46.0.dev0"
+  "transformers_version": "4.49.0.dev0"
 }