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tags: |
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- generated_from_trainer |
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datasets: |
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- coco |
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metrics: |
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- rouge |
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- bleu |
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model-index: |
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- name: IC_ver3b_coco_swin_gpt2_2 |
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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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# IC_ver3b_coco_swin_gpt2_2 |
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This model is a fine-tuned version of [](https://huggingface.co/) on the coco dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8483 |
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- Rouge1: 41.3447 |
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- Rouge2: 15.7294 |
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- Rougel: 37.6633 |
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- Rougelsum: 37.6744 |
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- Bleu: 9.4309 |
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- Gen Len: 11.3368 |
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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: 96 |
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- eval_batch_size: 96 |
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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 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:------:|:-------:| |
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| 1.2141 | 0.25 | 300 | 1.0093 | 35.2179 | 11.1228 | 32.1546 | 32.167 | 6.2018 | 11.3368 | |
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| 1.0037 | 0.51 | 600 | 0.9600 | 36.4586 | 11.8379 | 33.324 | 33.3342 | 7.0081 | 11.3368 | |
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| 0.9644 | 0.76 | 900 | 0.9303 | 38.5343 | 13.2266 | 35.2902 | 35.3055 | 7.539 | 11.3368 | |
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| 0.9367 | 1.02 | 1200 | 0.9004 | 39.2182 | 13.7589 | 35.7747 | 35.7799 | 7.6492 | 11.3368 | |
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| 0.8842 | 1.27 | 1500 | 0.8876 | 39.4537 | 14.1037 | 35.9758 | 35.9776 | 8.4067 | 11.3368 | |
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| 0.86 | 1.53 | 1800 | 0.8758 | 40.4179 | 15.0774 | 37.0166 | 37.0401 | 8.8897 | 11.3368 | |
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| 0.8465 | 1.78 | 2100 | 0.8665 | 40.4073 | 15.1125 | 36.9767 | 36.9877 | 8.9602 | 11.3368 | |
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| 0.8421 | 2.04 | 2400 | 0.8592 | 40.62 | 15.2042 | 36.9224 | 36.9359 | 9.1313 | 11.3368 | |
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| 0.8106 | 2.29 | 2700 | 0.8548 | 41.0356 | 15.399 | 37.4562 | 37.4635 | 9.2534 | 11.3368 | |
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| 0.7963 | 2.54 | 3000 | 0.8521 | 41.1998 | 15.6442 | 37.6659 | 37.6682 | 9.4605 | 11.3368 | |
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| 0.795 | 2.8 | 3300 | 0.8493 | 41.1215 | 15.581 | 37.4725 | 37.4978 | 9.5488 | 11.3368 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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