End of training

README.md

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+---
+language:
+- sw
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_15_0
+metrics:
+- wer
+model-index:
+- name: Incremental Swahili Luganda
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Mix data
+      type: mozilla-foundation/common_voice_15_0
+      config: lg
+      split: validation
+      args: 'config: lu, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 30.81815492541098
+---
+
+<!-- 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. -->
+
+# Incremental Swahili Luganda
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Mix data dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3450
+- Wer: 30.8182
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.1442        | 0.1129 | 500  | 0.3683          | 32.9502 |
+| 0.1532        | 0.2258 | 1000 | 0.3707          | 32.7589 |
+| 0.1478        | 0.3388 | 1500 | 0.3663          | 33.0019 |
+| 0.1375        | 0.4517 | 2000 | 0.3625          | 31.7817 |
+| 0.1509        | 0.5646 | 2500 | 0.3552          | 32.2106 |
+| 0.139         | 0.6775 | 3000 | 0.3510          | 31.5271 |
+| 0.1404        | 0.7904 | 3500 | 0.3473          | 30.9787 |
+| 0.1349        | 0.9033 | 4000 | 0.3450          | 30.8182 |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.2.2+cu118
+- Datasets 2.19.0
+- Tokenizers 0.19.1

generation_config.json

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+}