End of training

README.md

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+---
+library_name: transformers
+language:
+- sw
+license: apache-2.0
+base_model: openai/whisper-base
+tags:
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_17_0
+metrics:
+- wer
+model-index:
+- name: Whisper Base Swahili - Munene Mutuma
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 17.0
+      type: mozilla-foundation/common_voice_17_0
+      config: sw
+      split: None
+      args: 'config: sw, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 39.326889819760964
+---
+
+<!-- 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 Base Swahili - Munene Mutuma
+
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 17.0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6033
+- Wer: 39.3269
+
+## 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: 1e-05
+- train_batch_size: 64
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH 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
+- training_steps: 5000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.5121        | 1.0893 | 1000 | 0.7500          | 50.1768 |
+| 0.3802        | 2.1786 | 2000 | 0.6447          | 43.3016 |
+| 0.31          | 3.2680 | 3000 | 0.6139          | 39.4864 |
+| 0.2768        | 4.3573 | 4000 | 0.6029          | 39.2423 |
+| 0.266         | 5.4466 | 5000 | 0.6033          | 39.3269 |
+
+
+### Framework versions
+
+- Transformers 4.48.0
+- Pytorch 2.7.0a0+79aa17489c.nv25.04
+- Datasets 3.6.0
+- Tokenizers 0.21.4

config.json

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+{
+  "_name_or_path": "openai/whisper-base",
+  "activation_dropout": 0.0,
+  "activation_function": "gelu",
+  "apply_spec_augment": false,
+  "architectures": [
+    "WhisperForConditionalGeneration"
+  ],
+  "attention_dropout": 0.0,
+  "begin_suppress_tokens": null,
+  "bos_token_id": 50257,
+  "classifier_proj_size": 256,
+  "d_model": 512,
+  "decoder_attention_heads": 8,
+  "decoder_ffn_dim": 2048,
+  "decoder_layerdrop": 0.0,
+  "decoder_layers": 6,
+  "decoder_start_token_id": 50258,
+  "dropout": 0.0,
+  "encoder_attention_heads": 8,
+  "encoder_ffn_dim": 2048,
+  "encoder_layerdrop": 0.0,
+  "encoder_layers": 6,
+  "eos_token_id": 50257,
+  "forced_decoder_ids": [
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+      50259
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+    [
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+      50359
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+  "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_length": null,
+  "max_source_positions": 1500,
+  "max_target_positions": 448,
+  "median_filter_width": 7,
+  "model_type": "whisper",
+  "num_hidden_layers": 6,
+  "num_mel_bins": 80,
+  "pad_token_id": 50257,
+  "scale_embedding": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.48.0",
+  "use_cache": true,
+  "use_weighted_layer_sum": false,
+  "vocab_size": 51865
+}

generation_config.json

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