Model save

README.md

@@ -1,41 +1,40 @@
 ---
-language:
-- eu
+library_name: transformers
 license: apache-2.0
+base_model: openai/whisper-medium
 tags:
-- whisper-event
 - generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_16_0
+- common_voice_17_0
 metrics:
 - wer
 model-index:
-- name: Whisper Medium Basque
+- name: openai/whisper-medium
   results:
   - task:
       name: Automatic Speech Recognition
       type: automatic-speech-recognition
     dataset:
-      name: mozilla-foundation/common_voice_16_0 eu
-      type: mozilla-foundation/common_voice_16_0
+      name: common_voice_17_0
+      type: common_voice_17_0
       config: eu
       split: test
       args: eu
     metrics:
     - name: Wer
       type: wer
-      value: 9.188591686749389
+      value: 8.8020814247499
 ---
 
 <!-- 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 Medium Basque
+# openai/whisper-medium
 
-This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_16_0 eu dataset.
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the common_voice_17_0 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1503
-- Wer: 9.1886
+- Loss: 0.1787
+- Wer: 8.8021
 
 ## Model description
 
@@ -54,11 +53,11 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
-- train_batch_size: 4
+- learning_rate: 6.25e-06
+- train_batch_size: 16
 - eval_batch_size: 8
 - seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- 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
 - training_steps: 8000
@@ -66,29 +65,29 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.4647        | 0.06  | 500  | 0.4529          | 34.2140 |
-| 0.3163        | 0.12  | 1000 | 0.3516          | 26.0232 |
-| 0.3232        | 0.19  | 1500 | 0.2996          | 21.1825 |
-| 0.266         | 0.25  | 2000 | 0.2686          | 18.5126 |
-| 0.2383        | 0.31  | 2500 | 0.2489          | 16.9412 |
-| 0.1916        | 0.38  | 3000 | 0.2233          | 15.2831 |
-| 0.2009        | 0.44  | 3500 | 0.2134          | 14.1419 |
-| 0.2014        | 0.5   | 4000 | 0.2015          | 13.6579 |
-| 0.1964        | 0.56  | 4500 | 0.1853          | 12.0198 |
-| 0.1758        | 0.62  | 5000 | 0.1796          | 11.4651 |
-| 0.2067        | 0.69  | 5500 | 0.1679          | 10.7989 |
-| 0.213         | 0.75  | 6000 | 0.1618          | 10.3139 |
-| 0.1272        | 1.03  | 6500 | 0.1551          | 9.8687  |
-| 0.0744        | 1.09  | 7000 | 0.1534          | 9.5172  |
-| 0.0726        | 1.16  | 7500 | 0.1518          | 9.3240  |
-| 0.0627        | 1.22  | 8000 | 0.1503          | 9.1886  |
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.3171        | 0.0625 | 500  | 0.3369          | 25.5304 |
+| 0.1852        | 0.125  | 1000 | 0.2409          | 17.3110 |
+| 0.2353        | 0.1875 | 1500 | 0.2050          | 14.2228 |
+| 0.1569        | 1.037  | 2000 | 0.1815          | 12.2861 |
+| 0.125         | 1.0995 | 2500 | 0.1692          | 11.1144 |
+| 0.12          | 1.162  | 3000 | 0.1600          | 10.6975 |
+| 0.069         | 2.0115 | 3500 | 0.1540          | 9.7649  |
+| 0.0606        | 2.074  | 4000 | 0.1550          | 9.8199  |
+| 0.0434        | 2.1365 | 4500 | 0.1580          | 9.4571  |
+| 0.0455        | 2.199  | 5000 | 0.1533          | 9.1410  |
+| 0.0216        | 3.0485 | 5500 | 0.1620          | 9.0842  |
+| 0.017         | 3.111  | 6000 | 0.1704          | 9.0980  |
+| 0.0174        | 3.1735 | 6500 | 0.1681          | 9.0723  |
+| 0.0098        | 4.023  | 7000 | 0.1725          | 8.8625  |
+| 0.0076        | 4.0855 | 7500 | 0.1765          | 8.8351  |
+| 0.007         | 4.148  | 8000 | 0.1787          | 8.8021  |
 
 
 ### Framework versions
 
-- Transformers 4.26.0.dev0
-- Pytorch 1.13.1+cu117
-- Datasets 2.8.1.dev0
-- Tokenizers 0.13.2
+- Transformers 4.46.0.dev0
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.2.dev0
+- Tokenizers 0.20.0

generation_config.json

@@ -0,0 +1,248 @@
+{
+  "alignment_heads": [
+    [
+      13,
+      15
+    ],
+    [
+      15,
+      4
+    ],
+    [
+      15,
+      15
+    ],
+    [
+      16,
+      1
+    ],
+    [
+      20,
+      0
+    ],
+    [
+      23,
+      4
+    ]
+  ],
+  "begin_suppress_tokens": [
+    220,
+    50257
+  ],
+  "bos_token_id": 50257,
+  "decoder_start_token_id": 50258,
+  "eos_token_id": 50257,
+  "forced_decoder_ids": [
+    [
+      1,
+      null
+    ],
+    [
+      2,
+      50359
+    ]
+  ],
+  "is_multilingual": true,
+  "lang_to_id": {
+    "<|af|>": 50327,
+    "<|am|>": 50334,
+    "<|ar|>": 50272,
+    "<|as|>": 50350,
+    "<|az|>": 50304,
+    "<|ba|>": 50355,
+    "<|be|>": 50330,
+    "<|bg|>": 50292,
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+    "<|br|>": 50309,
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+    "<|de|>": 50261,
+    "<|el|>": 50281,
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+    "<|es|>": 50262,
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+    "<|eu|>": 50310,
+    "<|fa|>": 50300,
+    "<|fi|>": 50277,
+    "<|fo|>": 50338,
+    "<|fr|>": 50265,
+    "<|gl|>": 50319,
+    "<|gu|>": 50333,
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+    "<|tr|>": 50268,
+    "<|tt|>": 50351,
+    "<|uk|>": 50280,
+    "<|ur|>": 50290,
+    "<|uz|>": 50337,
+    "<|vi|>": 50278,
+    "<|yi|>": 50335,
+    "<|yo|>": 50325,
+    "<|zh|>": 50260
+  },
+  "max_initial_timestamp_index": 50,
+  "max_length": 448,
+  "no_timestamps_token_id": 50363,
+  "pad_token_id": 50257,
+  "prev_sot_token_id": 50361,
+  "return_timestamps": false,
+  "suppress_tokens": [
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+  "task_to_id": {
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+    "translate": 50358
+  },
+  "transformers_version": "4.46.0.dev0"
+}