Training in progress, step 25

README.md

@@ -3,6 +3,8 @@ license: apache-2.0
 library_name: peft
 tags:
 - generated_from_trainer
+datasets:
+- common_voice_16_1
 base_model: openai/whisper-small
 model-index:
 - name: whisper-small-finetuned-finetuned
@@ -14,15 +16,15 @@ should probably proofread and complete it, then remove this comment. -->
 
 # whisper-small-finetuned-finetuned
 
-This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_16_1 dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 2.6285
-- eval_wer: 117.5
-- eval_runtime: 31.5674
-- eval_samples_per_second: 0.19
-- eval_steps_per_second: 0.032
-- epoch: 199.0
-- step: 200
+- eval_loss: 2.3974
+- eval_wer: 218.1818
+- eval_runtime: 33.8002
+- eval_samples_per_second: 0.118
+- eval_steps_per_second: 0.03
+- epoch: 24.01
+- step: 25
 
 ## Model description
 
@@ -41,19 +43,19 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
+- learning_rate: 0.001
 - train_batch_size: 96
 - eval_batch_size: 64
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- training_steps: 200
+- training_steps: 100
 - mixed_precision_training: Native AMP
 
 ### Framework versions
 
 - PEFT 0.9.0
 - Transformers 4.39.2
-- Pytorch 2.2.1+cu121
+- Pytorch 2.2.2+cu121
 - Datasets 2.17.0
 - Tokenizers 0.15.2

adapter_config.json

@@ -22,8 +22,8 @@
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   "revision": null,
   "target_modules": [
-    "q_proj",
-    "v_proj"
+    "v_proj",
+    "q_proj"
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   "task_type": null,
   "use_dora": false,

adapter_model.bin

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