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---
library_name: transformers
license: apache-2.0
base_model: google/flan-t5-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: flanT5_Task2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# flanT5_Task2
This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1812
- Accuracy: 0.7706
- Precision: 0.7861
- Recall: 0.7435
- F1 score: 0.7642
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 score |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 1.1443 | 0.4205 | 2500 | 1.6635 | 0.6718 | 0.7829 | 0.4753 | 0.5915 |
| 1.0447 | 0.8410 | 5000 | 0.5585 | 0.7282 | 0.8149 | 0.5906 | 0.6849 |
| 0.9057 | 1.2616 | 7500 | 0.9051 | 0.7318 | 0.7275 | 0.7412 | 0.7343 |
| 0.8348 | 1.6821 | 10000 | 0.6307 | 0.7659 | 0.8742 | 0.6212 | 0.7263 |
| 0.7331 | 2.1026 | 12500 | 0.9500 | 0.7612 | 0.7489 | 0.7859 | 0.7669 |
| 0.6167 | 2.5231 | 15000 | 1.1524 | 0.7788 | 0.7970 | 0.7482 | 0.7718 |
| 0.6209 | 2.9437 | 17500 | 1.1690 | 0.7635 | 0.7872 | 0.7224 | 0.7534 |
| 0.4411 | 3.3642 | 20000 | 1.7563 | 0.7847 | 0.8438 | 0.6988 | 0.7645 |
| 0.4196 | 3.7847 | 22500 | 1.7767 | 0.7412 | 0.7204 | 0.7882 | 0.7528 |
| 0.292 | 4.2052 | 25000 | 2.0410 | 0.7624 | 0.7648 | 0.7576 | 0.7612 |
| 0.1791 | 4.6257 | 27500 | 2.1812 | 0.7706 | 0.7861 | 0.7435 | 0.7642 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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