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--- |
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license: apache-2.0 |
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base_model: jinaai/jina-embeddings-v2-base-code |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: jina_embeddings_v2_base_code_multi_regression-simple |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<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/nakztaik) |
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# jina_embeddings_v2_base_code_multi_regression-simple |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6201 |
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- Mse: 0.6201 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 90085 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-09 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mse | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 0.7241 | 0.1936 | 100 | 0.6361 | 0.6361 | |
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| 0.575 | 0.3871 | 200 | 0.6364 | 0.6364 | |
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| 0.6298 | 0.5807 | 300 | 0.6253 | 0.6253 | |
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| 0.4298 | 0.7743 | 400 | 0.6117 | 0.6117 | |
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| 0.5672 | 0.9678 | 500 | 0.6216 | 0.6216 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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