metadata
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
datasets:
- neulab/tldr
metrics:
- rouge
model-index:
- name: BASH-Coder-Flan-T5-base
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: tldr
type: tldr
config: data
split: validation
args: data
metrics:
- name: Rouge1
type: rouge
value: 27.0741
BASH-Coder-Flan-T5-base
This model is a fine-tuned version of google/flan-t5-base on the neulab/tldr dataset. It achieves the following results on the evaluation set:
- Loss: 3.3608
- Rouge1: 27.0741
- Rouge2: 9.3824
- Rougel: 26.133
- Rougelsum: 26.1559
- Gen Len: 15.5767
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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 4.3554 | 1.0 | 802 | 3.5928 | 22.7234 | 6.7951 | 22.0647 | 22.0744 | 15.2363 |
| 3.5335 | 2.0 | 1604 | 3.4654 | 25.7842 | 8.5847 | 24.8207 | 24.8808 | 15.168 |
| 3.3341 | 3.0 | 2406 | 3.4078 | 25.5756 | 8.4456 | 24.706 | 24.7207 | 15.6472 |
| 3.2011 | 4.0 | 3208 | 3.3789 | 26.0638 | 8.6853 | 25.0862 | 25.1223 | 16.2748 |
| 3.1059 | 5.0 | 4010 | 3.3622 | 26.7254 | 9.1138 | 25.7985 | 25.8521 | 15.7366 |
| 3.0336 | 6.0 | 4812 | 3.3662 | 26.4655 | 9.1283 | 25.4587 | 25.5112 | 16.548 |
| 2.9727 | 7.0 | 5614 | 3.3593 | 26.8211 | 9.3045 | 25.8497 | 25.8772 | 15.5431 |
| 2.9298 | 8.0 | 6416 | 3.3643 | 26.8932 | 9.3537 | 25.9444 | 26.0088 | 15.916 |
| 2.9005 | 9.0 | 7218 | 3.3606 | 27.1732 | 9.5661 | 26.1198 | 26.1515 | 15.71 |
| 2.8846 | 10.0 | 8020 | 3.3608 | 27.0741 | 9.3824 | 26.133 | 26.1559 | 15.5767 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0