File size: 3,526 Bytes
6647bd5 |
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 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 |
---
license: apache-2.0
base_model: t5-3b
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: t5-3b_rte_sp0_ar0
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: rte
split: validation
args: rte
metrics:
- name: Accuracy
type: accuracy
value: 0.8995983935742972
---
<!-- 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. -->
# t5-3b_rte_sp0_ar0
This model is a fine-tuned version of [t5-3b](https://huggingface.co/t5-3b) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4886
- Accuracy: 0.8996
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 1
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 750
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7116 | 0.18 | 25 | 0.7078 | 0.4838 |
| 0.615 | 0.36 | 50 | 0.4571 | 0.8484 |
| 0.501 | 0.53 | 75 | 0.4176 | 0.8484 |
| 0.337 | 0.71 | 100 | 0.4462 | 0.8809 |
| 0.4199 | 0.89 | 125 | 0.4309 | 0.7942 |
| 0.2477 | 1.07 | 150 | 0.4325 | 0.8881 |
| 0.2253 | 1.25 | 175 | 0.4596 | 0.8845 |
| 0.214 | 1.42 | 200 | 0.9106 | 0.8736 |
| 0.2577 | 1.6 | 225 | 0.3652 | 0.9025 |
| 0.1966 | 1.78 | 250 | 0.3645 | 0.9097 |
| 0.2278 | 1.96 | 275 | 0.3337 | 0.9206 |
| 0.1221 | 2.14 | 300 | 1.2373 | 0.8881 |
| 0.3576 | 2.31 | 325 | 2.0514 | 0.8809 |
| 0.6186 | 2.49 | 350 | 3.9886 | 0.8809 |
| 1.0915 | 2.67 | 375 | 3.3403 | 0.8845 |
| 0.321 | 2.85 | 400 | 4.6906 | 0.8989 |
| 0.3969 | 3.02 | 425 | 1.2608 | 0.8736 |
| 0.026 | 3.2 | 450 | 4.4563 | 0.8809 |
| 0.0695 | 3.38 | 475 | 4.6858 | 0.8917 |
| 0.7626 | 3.56 | 500 | 4.7502 | 0.8917 |
| 0.2675 | 3.74 | 525 | 5.0576 | 0.9025 |
| 0.82 | 3.91 | 550 | 3.6297 | 0.9025 |
| 0.0011 | 4.09 | 575 | 5.7629 | 0.8989 |
| 0.3 | 4.27 | 600 | 2.3117 | 0.9097 |
| 0.0544 | 4.45 | 625 | 1.5657 | 0.9097 |
| 0.2907 | 4.63 | 650 | 2.6475 | 0.9025 |
| 0.2868 | 4.8 | 675 | 2.6720 | 0.8989 |
| 0.3191 | 4.98 | 700 | 2.8372 | 0.8773 |
| 0.0382 | 5.16 | 725 | 6.0565 | 0.9025 |
| 0.0297 | 5.34 | 750 | 4.1639 | 0.8736 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
|