| --- |
| license: apache-2.0 |
| base_model: jinaai/jina-embeddings-v2-base-code |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: jina_embeddings_v2_base_code_multi_regression-simple |
| 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. --> |
|
|
| [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amazingvince/huggingface/runs/atvo6d3z) |
| # jina_embeddings_v2_base_code_multi_regression-simple |
|
|
| This model is a fine-tuned version of [jinaai/jina-embeddings-v2-base-code](https://huggingface.co/jinaai/jina-embeddings-v2-base-code) on the amazingvince/the-stack-smol-xs-scored-and-annotated-all dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6115 |
| - Mse: 0.6115 |
|
|
| ## Model description |
|
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| More information needed |
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| ## Intended uses & limitations |
|
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| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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| The following hyperparameters were used during training: |
| - learning_rate: 1e-05 |
| - train_batch_size: 2 |
| - eval_batch_size: 2 |
| - seed: 90085 |
| - distributed_type: multi-GPU |
| - gradient_accumulation_steps: 32 |
| - total_train_batch_size: 64 |
| - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-09 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.05 |
| - num_epochs: 3.0 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Mse | |
| |:-------------:|:------:|:----:|:---------------:|:------:| |
| | 0.5611 | 0.7743 | 100 | 0.6137 | 0.6137 | |
| | 0.6542 | 1.5485 | 200 | 0.6139 | 0.6139 | |
| | 0.5106 | 2.3228 | 300 | 0.6125 | 0.6125 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.4 |
| - Pytorch 2.1.1+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
