End of training

README.md

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+---
+library_name: peft
+language:
+- en
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- generated_from_trainer
+datasets:
+- mesolitica/IMDA-TTS
+metrics:
+- wer
+model-index:
+- name: Whisper Small NSC small (500 steps) - Jarrett Er
+  results:
+  - task:
+      type: automatic-speech-recognition
+      name: Automatic Speech Recognition
+    dataset:
+      name: NSC Small section
+      type: mesolitica/IMDA-TTS
+      split: None
+      args: 'config: en, split: train'
+    metrics:
+    - type: wer
+      value: 4.936854190585533
+      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 Small NSC small (500 steps) - Jarrett Er
+
+This model is a fine-tuned version of [Thecoder3281f/whisper-small-hi-commonvoice17-1000](https://huggingface.co/Thecoder3281f/whisper-small-hi-commonvoice17-1000) on the NSC Small section dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1036
+- Wer: 4.9369
+
+## 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: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 50
+- training_steps: 500
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer    |
+|:-------------:|:------:|:----:|:---------------:|:------:|
+| 0.0718        | 1.7544 | 100  | 0.0956          | 5.9701 |
+| 0.0226        | 3.5088 | 200  | 0.0991          | 5.2813 |
+| 0.0077        | 5.2632 | 300  | 0.1004          | 4.3628 |
+| 0.0052        | 7.0175 | 400  | 0.1026          | 4.9369 |
+| 0.0042        | 8.7719 | 500  | 0.1036          | 4.9369 |
+
+
+### Framework versions
+
+- PEFT 0.14.0
+- Transformers 4.45.2
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.1.dev0
+- Tokenizers 0.20.3

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": {
+    "base_model_class": "PeftModel",
+    "parent_library": "peft.peft_model"
+  },
+  "base_model_name_or_path": null,
+  "bias": "none",
+  "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",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "down_proj",
+    "v_proj",
+    "k_proj",
+    "q_proj",
+    "o_proj",
+    "up_proj",
+    "gate_proj"
+  ],
+  "task_type": null,
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 13035080

preprocessor_config.json

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+{
+  "chunk_length": 30,
+  "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
+}

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training_args.bin

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