dmusingu
/

WHISPER-MEDIUM-LUGANDA-ASR-CV-14

@@ -1,201 +1,88 @@
 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
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 ---
+language:
+- sw
+license: apache-2.0
+base_model: openai/whisper-large
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_14_0
+metrics:
+- wer
+model-index:
+- name: Whisper Large  - Denis Musinguzi
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 14.0
+      type: mozilla-foundation/common_voice_14_0
+      config: lg
+      split: None
+      args: 'config: sw, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.24669449134992194
 ---
+<!-- 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 Large  - Denis Musinguzi
+This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Common Voice 14.0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2966
+- Wer: 0.2467
+- Cer: 0.0700
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 10000
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step | Cer    | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:------:|:---------------:|:------:|
+| 0.6329        | 0.61  | 1600 | 0.0878 | 0.3515          | 0.3385 |
+| 0.2241        | 1.22  | 3200 | 0.0589 | 0.3045          | 0.2517 |
+| 0.1618        | 1.82  | 4800 | 0.0707 | 0.2801          | 0.2645 |
+| 0.1109        | 2.43  | 6400 | 0.0774 | 0.2870          | 0.2580 |
+| 0.0837        | 3.04  | 8000 | 0.0597 | 0.2900          | 0.2333 |
+| 0.045         | 3.65  | 9600 | 0.2966 | 0.2467          | 0.0700 |
+### Framework versions
+- Transformers 4.38.1
+- Pytorch 2.2.1
+- Datasets 2.17.0
+- Tokenizers 0.15.2

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+}

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