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--- |
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license: apache-2.0 |
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base_model: Qwen/Qwen2.5-0.5B-Instruct |
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tags: |
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- generated_from_trainer |
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datasets: |
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- wikitext |
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metrics: |
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- accuracy |
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model-index: |
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- name: llm2vec-qwen2.5-0.5-instruct |
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results: |
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- task: |
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name: Masked Language Modeling |
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type: fill-mask |
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dataset: |
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name: wikitext wikitext-103-raw-v1 |
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type: wikitext |
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args: wikitext-103-raw-v1 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.629556877924779 |
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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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# llm2vec-qwen2.5-0.5-instruct |
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This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co./Qwen/Qwen2.5-0.5B-Instruct) on the wikitext wikitext-103-raw-v1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8264 |
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- Accuracy: 0.6296 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| No log | 0.0083 | 100 | 2.3376 | 0.5511 | |
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| No log | 0.0166 | 200 | 2.1736 | 0.5765 | |
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| No log | 0.0248 | 300 | 2.0679 | 0.5930 | |
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| No log | 0.0331 | 400 | 1.9839 | 0.6056 | |
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| 2.2761 | 0.0414 | 500 | 1.9611 | 0.6085 | |
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| 2.2761 | 0.0497 | 600 | 1.9054 | 0.6203 | |
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| 2.2761 | 0.0580 | 700 | 1.8838 | 0.6242 | |
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| 2.2761 | 0.0662 | 800 | 1.8403 | 0.6296 | |
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| 2.2761 | 0.0745 | 900 | 1.8235 | 0.6300 | |
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| 1.8887 | 0.0828 | 1000 | 1.7920 | 0.6351 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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