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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: t5_recommendation_sports_equipment_english |
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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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# t5_recommendation_sports_equipment_english |
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This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4438 |
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- Rouge1: 72.2222 |
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- Rouge2: 66.6667 |
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- Rougel: 72.2222 |
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- Rougelsum: 72.2222 |
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- Gen Len: 4.0952 |
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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: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 40 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| No log | 1.0 | 1 | 9.9716 | 12.6943 | 0.0 | 12.4298 | 12.3728 | 19.0 | |
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| No log | 2.0 | 2 | 10.1466 | 10.0457 | 0.0 | 9.8413 | 9.8341 | 19.0 | |
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| No log | 3.0 | 3 | 8.3378 | 10.7204 | 0.0 | 10.4782 | 10.4681 | 19.0 | |
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| No log | 4.0 | 4 | 7.3021 | 10.7204 | 0.0 | 10.4782 | 10.4681 | 19.0 | |
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| No log | 5.0 | 5 | 6.3242 | 10.5739 | 0.0 | 10.3628 | 10.3550 | 19.0 | |
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| No log | 6.0 | 6 | 5.4331 | 10.3340 | 0.7937 | 10.3340 | 10.2659 | 19.0 | |
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| No log | 7.0 | 7 | 4.7152 | 10.8955 | 0.7937 | 10.9896 | 10.8598 | 18.9524 | |
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| No log | 8.0 | 8 | 3.9937 | 14.1311 | 3.5923 | 14.2840 | 13.9026 | 15.0952 | |
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| No log | 9.0 | 9 | 3.1163 | 16.2812 | 1.0025 | 16.1905 | 16.0614 | 6.4762 | |
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| No log | 10.0 | 10 | 2.3306 | 23.1746 | 7.1429 | 23.1746 | 23.6508 | 4.1429 | |
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| No log | 11.0 | 11 | 1.9695 | 21.4286 | 7.1429 | 21.4286 | 21.7460 | 4.0476 | |
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| No log | 12.0 | 12 | 1.5552 | 24.1270 | 7.1429 | 23.9683 | 24.1270 | 3.9048 | |
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| No log | 13.0 | 13 | 0.8986 | 9.0476 | 0.0 | 9.0476 | 9.0476 | 3.7619 | |
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| No log | 14.0 | 14 | 0.7398 | 18.2540 | 2.3810 | 18.2540 | 18.2540 | 4.1905 | |
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| No log | 15.0 | 15 | 0.6966 | 12.6984 | 0.0 | 11.9048 | 12.6984 | 3.6667 | |
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| No log | 16.0 | 16 | 0.6352 | 32.5397 | 14.2857 | 32.5397 | 31.7460 | 3.7619 | |
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| No log | 17.0 | 17 | 0.5722 | 43.6508 | 23.8095 | 43.6508 | 43.6508 | 4.0952 | |
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| No log | 18.0 | 18 | 0.5628 | 43.6508 | 23.8095 | 43.6508 | 43.6508 | 3.8571 | |
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| No log | 19.0 | 19 | 0.5526 | 43.1746 | 23.8095 | 43.0159 | 42.8571 | 3.8571 | |
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| No log | 20.0 | 20 | 0.5522 | 48.4127 | 38.0952 | 48.4127 | 48.4127 | 3.7619 | |
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| No log | 21.0 | 21 | 0.5201 | 42.8571 | 28.5714 | 42.6190 | 42.6984 | 4.2381 | |
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| No log | 22.0 | 22 | 0.5262 | 36.9841 | 19.0476 | 36.9841 | 36.9841 | 4.2857 | |
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| No log | 23.0 | 23 | 0.5093 | 38.0952 | 23.8095 | 37.5397 | 37.9365 | 4.1429 | |
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| No log | 24.0 | 24 | 0.4818 | 45.6349 | 33.3333 | 45.0794 | 45.3968 | 4.1429 | |
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| No log | 25.0 | 25 | 0.4547 | 50.7937 | 38.0952 | 50.0 | 50.7937 | 4.1429 | |
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| No log | 26.0 | 26 | 0.4455 | 50.7937 | 38.0952 | 50.0 | 50.7937 | 4.1429 | |
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| No log | 27.0 | 27 | 0.4660 | 53.1746 | 42.8571 | 53.1746 | 53.1746 | 4.0476 | |
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| No log | 28.0 | 28 | 0.4825 | 53.1746 | 42.8571 | 53.1746 | 53.1746 | 4.0 | |
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| No log | 29.0 | 29 | 0.4928 | 53.1746 | 42.8571 | 53.1746 | 53.1746 | 4.0476 | |
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| No log | 30.0 | 30 | 0.4838 | 57.4603 | 42.8571 | 57.1429 | 57.1429 | 4.0476 | |
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| No log | 31.0 | 31 | 0.4955 | 60.3175 | 47.6190 | 60.3175 | 60.3175 | 4.0476 | |
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| No log | 32.0 | 32 | 0.5066 | 62.6984 | 52.3810 | 62.6984 | 62.6984 | 4.1429 | |
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| No log | 33.0 | 33 | 0.5189 | 62.6984 | 52.3810 | 62.6984 | 62.6984 | 4.1905 | |
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| No log | 34.0 | 34 | 0.5234 | 62.6984 | 52.3810 | 62.6984 | 62.6984 | 4.1905 | |
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| No log | 35.0 | 35 | 0.5225 | 62.6984 | 52.3810 | 62.6984 | 62.6984 | 4.1905 | |
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| No log | 36.0 | 36 | 0.5225 | 62.6984 | 52.3810 | 62.6984 | 62.6984 | 4.1905 | |
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| No log | 37.0 | 37 | 0.5058 | 62.2222 | 52.3810 | 61.9048 | 61.9048 | 4.1429 | |
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| No log | 38.0 | 38 | 0.4861 | 70.6349 | 61.9048 | 69.8413 | 69.8413 | 4.1905 | |
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| No log | 39.0 | 39 | 0.4625 | 70.6349 | 61.9048 | 69.8413 | 69.8413 | 4.1905 | |
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| No log | 40.0 | 40 | 0.4438 | 72.2222 | 66.6667 | 72.2222 | 72.2222 | 4.0952 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.3 |
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