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rohitsaxena
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sft-llava-1.5-7b-hf3

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sft
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Files changed (20) hide show
  1. README.md +86 -0
  2. added_tokens.json +4 -0
  3. config.json +178 -0
  4. generation_config.json +7 -0
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  6. model-00002-of-00003.safetensors +3 -0
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  9. runs/Oct21_18-58-57_s1840377-6-88zz2/events.out.tfevents.1729537157.s1840377-6-88zz2.888278.0 +3 -0
  10. runs/Oct21_19-00-00_s1840377-6-88zz2/events.out.tfevents.1729537222.s1840377-6-88zz2.889658.0 +3 -0
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  12. runs/Oct21_19-03-09_s1840377-6-88zz2/events.out.tfevents.1729537411.s1840377-6-88zz2.892748.0 +3 -0
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  14. runs/Oct21_22-46-38_s1840377-6-88zz2/events.out.tfevents.1729550826.s1840377-6-88zz2.922803.0 +3 -0
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  16. test_predictions.pkl +3 -0
  17. tokenizer.json +0 -0
  18. tokenizer.model +3 -0
  19. tokenizer_config.json +60 -0
  20. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: llama2
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+ base_model: llava-hf/llava-1.5-7b-hf
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+ tags:
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+ - trl
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+ - sft
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+ - generated_from_trainer
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+ metrics:
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+ - bleu
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+ - rouge
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+ model-index:
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+ - name: sft-llava-1.5-7b-hf3
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+ results: []
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+ ---
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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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+
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+ # sft-llava-1.5-7b-hf3
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+
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+ This model is a fine-tuned version of [llava-hf/llava-1.5-7b-hf](https://huggingface.co/llava-hf/llava-1.5-7b-hf) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 13.1181
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+ - Bleu: 0.0
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+ - Rouge1: 0.0651
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+ - Rouge2: 0.0043
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+ - Rougel: 0.0508
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+ - Bertscore Precision: 0.6243
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+ - Bertscore Recall: 0.7482
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+ - Bertscore F1: 0.6806
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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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+ - lr_scheduler_warmup_ratio: 0.03
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+ - num_epochs: 5.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge1 | Rouge2 | Rougel | Bertscore Precision | Bertscore Recall | Bertscore F1 |
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+ |:-------------:|:------:|:----:|:---------------:|:----:|:------:|:------:|:------:|:-------------------:|:----------------:|:------------:|
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+ | 6.903 | 0.3101 | 200 | 22.1793 | 0.0 | 0.0440 | 0.0 | 0.0441 | 0.6243 | 0.7482 | 0.6806 |
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+ | 6.585 | 0.6202 | 400 | 27.3559 | 0.0 | 0.0546 | 0.0043 | 0.0425 | 0.6243 | 0.7482 | 0.6806 |
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+ | 6.5197 | 0.9302 | 600 | 26.1987 | 0.0 | 0.0546 | 0.0043 | 0.0425 | 0.6243 | 0.7482 | 0.6806 |
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+ | 6.2662 | 1.2403 | 800 | 21.1666 | 0.0 | 0.0633 | 0.0043 | 0.0520 | 0.6243 | 0.7482 | 0.6806 |
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+ | 6.0303 | 1.5504 | 1000 | 21.0359 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 |
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+ | 5.7602 | 1.8605 | 1200 | 19.0201 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 |
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+ | 5.6359 | 2.1705 | 1400 | 18.6311 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 |
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+ | 5.5176 | 2.4806 | 1600 | 17.9442 | 0.0 | 0.0649 | 0.0043 | 0.0496 | 0.6243 | 0.7482 | 0.6806 |
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+ | 5.4608 | 2.7907 | 1800 | 16.6921 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 |
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+ | 5.2881 | 3.1008 | 2000 | 15.3415 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 |
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+ | 5.2429 | 3.4109 | 2200 | 14.8475 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 |
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+ | 5.1929 | 3.7209 | 2400 | 14.2828 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 |
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+ | 5.1259 | 4.0310 | 2600 | 13.8075 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 |
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+ | 5.0379 | 4.3411 | 2800 | 13.4751 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 |
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+ | 5.1071 | 4.6512 | 3000 | 13.2275 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 |
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+ | 5.1082 | 4.9612 | 3200 | 13.1181 | 0.0 | 0.0651 | 0.0043 | 0.0508 | 0.6243 | 0.7482 | 0.6806 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.2
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+ - Pytorch 2.2.0a0+81ea7a4
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.1
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