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The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
CBERT-MBPP
This model is a fine-tuned version of microsoft/codebert-base-mlm on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0099
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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0215 | 0.05 | 500 | 0.0196 |
| 0.0087 | 0.1 | 1000 | 0.0091 |
| 0.0093 | 0.15 | 1500 | 0.0090 |
| 0.0096 | 0.2 | 2000 | 0.0094 |
| 0.009 | 0.25 | 2500 | 0.0095 |
| 0.01 | 0.3 | 3000 | 0.0091 |
| 0.01 | 0.35 | 3500 | 0.0093 |
| 0.0093 | 0.4 | 4000 | 0.0094 |
| 0.0086 | 0.45 | 4500 | 0.0098 |
| 0.0085 | 0.5 | 5000 | 0.0097 |
| 0.0094 | 0.55 | 5500 | 0.0099 |
| 0.0099 | 0.6 | 6000 | 0.0101 |
| 0.0096 | 0.65 | 6500 | 0.0099 |
| 0.0104 | 0.7 | 7000 | 0.0099 |
| 0.0096 | 0.75 | 7500 | 0.0097 |
| 0.0087 | 0.8 | 8000 | 0.0098 |
| 0.0105 | 0.85 | 8500 | 0.0099 |
| 0.0098 | 0.9 | 9000 | 0.0098 |
| 0.0091 | 0.95 | 9500 | 0.0099 |
| 0.0101 | 1.0 | 10000 | 0.0099 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for AdnanRiaz107/CBERT-MBPP
Base model
microsoft/codebert-base-mlm