End of training

README.md

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+---
+library_name: peft
+language:
+- nl
+license: apache-2.0
+base_model: openai/whisper-large-v2
+tags:
+- base_model:adapter:openai/whisper-large-v2
+- lora
+- transformers
+datasets:
+- jasmin
+- jasmin-cgn
+metrics:
+- wer
+model-index:
+- name: whisper-new-nnat-5h-mmr-ecapa
+  results:
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: JASMIN-CGN
+      type: jasmin
+    metrics:
+    - type: wer
+      value: 35.10513745141198
+      name: Wer
+---
+
+<!-- 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-new-nnat-5h-mmr-ecapa
+
+This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the JASMIN-CGN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5545
+- Wer: 35.1051
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 48
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use adamw_torch_fused 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: 62
+- num_epochs: 3.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.9171        | 0.2967 | 62   | 0.7342          | 44.3497 |
+| 0.377         | 0.5933 | 124  | 0.6011          | 41.0902 |
+| 0.3449        | 0.8900 | 186  | 0.5843          | 42.5420 |
+| 0.315         | 1.1866 | 248  | 0.5710          | 39.1186 |
+| 0.2988        | 1.4833 | 310  | 0.5689          | 45.5393 |
+| 0.2893        | 1.7799 | 372  | 0.5588          | 37.1330 |
+| 0.2607        | 2.0766 | 434  | 0.5569          | 36.0230 |
+| 0.2532        | 2.3732 | 496  | 0.5575          | 35.7046 |
+| 0.2599        | 2.6699 | 558  | 0.5543          | 34.4776 |
+| 0.2716        | 2.9665 | 620  | 0.5545          | 35.1051 |
+
+
+### Framework versions
+
+- PEFT 0.17.1
+- Transformers 4.57.6
+- Pytorch 2.8.0+cu128
+- Datasets 4.5.0
+- Tokenizers 0.22.2

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": {
+    "base_model_class": "WhisperForConditionalGeneration",
+    "parent_library": "transformers.models.whisper.modeling_whisper"
+  },
+  "base_model_name_or_path": "openai/whisper-large-v2",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 64,
+  "lora_bias": false,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "target_parameters": null,
+  "task_type": null,
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 62969640

preprocessor_config.json

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+{
+  "chunk_length": 30,
+  "dither": 0.0,
+  "feature_extractor_type": "WhisperFeatureExtractor",
+  "feature_size": 80,
+  "hop_length": 160,
+  "n_fft": 400,
+  "n_samples": 480000,
+  "nb_max_frames": 3000,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "processor_class": "WhisperProcessor",
+  "return_attention_mask": false,
+  "sampling_rate": 16000
+}

training_args.bin

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