Efik ASR fine-tuned from whisper-small

README.md

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+---
+library_name: transformers
+base_model: offiongbassey/efik-asr
+tags:
+- generated_from_trainer
+model-index:
+- name: efik-whisper
+  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. -->
+
+# efik-whisper
+
+This model is a fine-tuned version of [offiongbassey/efik-asr](https://huggingface.co/offiongbassey/efik-asr) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1576
+
+## 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: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Use OptimizerNames.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: 500
+- num_epochs: 6
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.2799        | 0.4193 | 100  | 0.1487          |
+| 0.2567        | 0.8386 | 200  | 0.1377          |
+| 0.1838        | 1.2558 | 300  | 0.1434          |
+| 0.1970        | 1.6751 | 400  | 0.1477          |
+| 0.1627        | 2.0922 | 500  | 0.1550          |
+| 0.1272        | 2.5115 | 600  | 0.1520          |
+| 1.0981        | 2.9308 | 700  | 0.6144          |
+| 0.1212        | 3.3480 | 800  | 0.1595          |
+| 0.1055        | 3.7673 | 900  | 0.1635          |
+| 0.0623        | 4.1845 | 1000 | 0.1671          |
+| 0.0628        | 4.6038 | 1100 | 0.1620          |
+| 0.0478        | 5.0210 | 1200 | 0.1571          |
+| 0.0327        | 5.4403 | 1300 | 0.1598          |
+| 0.0241        | 5.8595 | 1400 | 0.1576          |
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.10.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.2

config.json

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+{
+  "activation_dropout": 0.0,
+  "activation_function": "gelu",
+  "apply_spec_augment": false,
+  "architectures": [
+    "WhisperForConditionalGeneration"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 50257,
+  "classifier_proj_size": 256,
+  "d_model": 768,
+  "decoder_attention_heads": 12,
+  "decoder_ffn_dim": 3072,
+  "decoder_layerdrop": 0.0,
+  "decoder_layers": 12,
+  "decoder_start_token_id": 50258,
+  "dropout": 0.0,
+  "dtype": "float32",
+  "encoder_attention_heads": 12,
+  "encoder_ffn_dim": 3072,
+  "encoder_layerdrop": 0.0,
+  "encoder_layers": 12,
+  "eos_token_id": 50257,
+  "forced_decoder_ids": null,
+  "init_std": 0.02,
+  "is_encoder_decoder": true,
+  "mask_feature_length": 10,
+  "mask_feature_min_masks": 0,
+  "mask_feature_prob": 0.0,
+  "mask_time_length": 10,
+  "mask_time_min_masks": 2,
+  "mask_time_prob": 0.05,
+  "max_source_positions": 1500,
+  "max_target_positions": 448,
+  "median_filter_width": 7,
+  "model_type": "whisper",
+  "num_hidden_layers": 12,
+  "num_mel_bins": 80,
+  "pad_token_id": 50257,
+  "scale_embedding": false,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.0.0",
+  "use_cache": false,
+  "use_weighted_layer_sum": false,
+  "vocab_size": 51865
+}

generation_config.json

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+      3
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+    50257
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+  "bos_token_id": 50257,
+  "decoder_start_token_id": 50258,
+  "eos_token_id": [
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+  "no_timestamps_token_id": 50363,
+  "pad_token_id": 50257,
+  "prev_sot_token_id": 50361,
+  "return_timestamps": false,
+  "suppress_tokens": [],
+  "task_to_id": {
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+    "translate": 50358
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+  "transformers_version": "5.0.0"
+}

model.safetensors

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training_args.bin

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