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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: flan-t5-base-absa-multitask-joint |
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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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# flan-t5-base-absa-multitask-joint |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1276 |
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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: 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: 0.1 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.5367 | 0.16 | 200 | 0.5267 | |
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| 0.5433 | 0.32 | 400 | 0.3377 | |
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| 0.3887 | 0.47 | 600 | 0.2688 | |
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| 0.3123 | 0.63 | 800 | 0.2205 | |
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| 0.2724 | 0.79 | 1000 | 0.2282 | |
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| 0.2627 | 0.95 | 1200 | 0.1881 | |
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| 0.2294 | 1.11 | 1400 | 0.1827 | |
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| 0.2221 | 1.27 | 1600 | 0.1844 | |
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| 0.1957 | 1.42 | 1800 | 0.1860 | |
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| 0.2007 | 1.58 | 2000 | 0.1674 | |
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| 0.1866 | 1.74 | 2200 | 0.1628 | |
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| 0.175 | 1.9 | 2400 | 0.1636 | |
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| 0.1637 | 2.06 | 2600 | 0.1506 | |
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| 0.1541 | 2.22 | 2800 | 0.1505 | |
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| 0.1484 | 2.37 | 3000 | 0.1465 | |
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| 0.1442 | 2.53 | 3200 | 0.1496 | |
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| 0.1338 | 2.69 | 3400 | 0.1355 | |
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| 0.1415 | 2.85 | 3600 | 0.1369 | |
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| 0.1435 | 3.01 | 3800 | 0.1343 | |
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| 0.1242 | 3.16 | 4000 | 0.1348 | |
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| 0.1227 | 3.32 | 4200 | 0.1328 | |
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| 0.1229 | 3.48 | 4400 | 0.1287 | |
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| 0.1272 | 3.64 | 4600 | 0.1280 | |
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| 0.1132 | 3.8 | 4800 | 0.1264 | |
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| 0.1131 | 3.96 | 5000 | 0.1276 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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