End of training

README.md

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+---
+language:
+- id
+license: apache-2.0
+library_name: peft
+tags:
+- id-asr-leaderboard
+- generated_from_trainer
+datasets:
+- '-'
+base_model: openai/whisper-large-v2
+model-index:
+- name: zeon8985army/KhalsuuTagalog-fineTunedLargeV2-tl-1
+  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. -->
+
+# zeon8985army/KhalsuuTagalog-fineTunedLargeV2-tl-1
+
+This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the AlistairBegg dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2708
+
+## 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: 6e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 12
+- training_steps: 276
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 3.26          | 0.05  | 12   | 3.5752          |
+| 2.9122        | 0.1   | 24   | 2.9222          |
+| 2.1061        | 0.15  | 36   | 1.9585          |
+| 1.6265        | 0.2   | 48   | 1.5771          |
+| 1.3155        | 0.25  | 60   | 1.3177          |
+| 1.1793        | 0.3   | 72   | 1.1780          |
+| 1.0208        | 0.35  | 84   | 1.0613          |
+| 0.9111        | 0.4   | 96   | 0.9361          |
+| 0.8078        | 0.44  | 108  | 0.7634          |
+| 0.6103        | 0.49  | 120  | 0.4794          |
+| 0.3911        | 0.54  | 132  | 0.2857          |
+| 0.324         | 0.59  | 144  | 0.2915          |
+| 0.3228        | 0.64  | 156  | 0.2858          |
+| 0.3103        | 0.69  | 168  | 0.2778          |
+| 0.3458        | 0.74  | 180  | 0.2750          |
+| 0.3283        | 0.79  | 192  | 0.2738          |
+| 0.394         | 0.84  | 204  | 0.2728          |
+| 0.3181        | 0.89  | 216  | 0.2711          |
+| 0.3201        | 0.94  | 228  | 0.2704          |
+| 0.3291        | 0.99  | 240  | 0.2705          |
+| 0.3084        | 1.04  | 252  | 0.2709          |
+| 0.32          | 1.09  | 264  | 0.2711          |
+| 0.363         | 1.14  | 276  | 0.2708          |
+
+
+### Framework versions
+
+- PEFT 0.9.0
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 64,
+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": null,
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+size 62969640

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
+}

runs/Mar24_16-19-55_93b2e1b2155b/events.out.tfevents.1711297201.93b2e1b2155b.24502.0

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training_args.bin

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