File size: 1,964 Bytes
ab0aec5 648da50 ab0aec5 648da50 ab0aec5 648da50 ab0aec5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 |
---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-base-pos2neg
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. -->
# t5-base-pos2neg
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1630
- Rouge1: 66.0728
- Rouge2: 48.2651
- Rougel: 65.0881
- Rougelsum: 64.9953
- Gen Len: 14.0178
## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log | 1.0 | 63 | 0.3641 | 6.8173 | 2.0998 | 6.622 | 6.5952 | 4.2956 |
| No log | 2.0 | 126 | 0.2475 | 0.5115 | 0.4098 | 0.4238 | 0.4359 | 0.1267 |
| No log | 3.0 | 189 | 0.1762 | 51.2946 | 37.2414 | 50.0953 | 49.9607 | 11.5711 |
| No log | 4.0 | 252 | 0.1653 | 64.4676 | 46.8688 | 63.3822 | 63.338 | 13.6889 |
| No log | 5.0 | 315 | 0.1630 | 66.0728 | 48.2651 | 65.0881 | 64.9953 | 14.0178 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.19.1
|