|
|
--- |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: Nato-chat |
|
|
results: [] |
|
|
|
|
|
language: |
|
|
- en |
|
|
|
|
|
widget: |
|
|
- text: "What is the Full form of NATO?" |
|
|
example_title: "Full Form" |
|
|
- text: "Name the NATO member countries." |
|
|
example_title: 'NATO Members' |
|
|
- text: "What kind of support did Ukraine offer to NATO?" |
|
|
example_title: 'Example 1' |
|
|
- text: 'Which country withdrew from the integrated military command of NATO in 1966?' |
|
|
example_title: 'Example 2' |
|
|
- text: 'Who were the original members of NATO' |
|
|
example_title: 'OG Members' |
|
|
- text: 'When was NATO established?' |
|
|
example_title: 'Example 3' |
|
|
- text: 'How many NATO members are there currently?' |
|
|
example_title: 'Example 4' |
|
|
- text: 'Who are the representatives of NATO member countries?' |
|
|
example_title: 'Example 5' |
|
|
- text: 'Question: What is the aim of the Mediterranean Dialogue?' |
|
|
example_title: 'Example 6' |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
inference: |
|
|
parameters: |
|
|
max_length: 600 |
|
|
|
|
|
|
|
|
--- |
|
|
<!-- 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. --> |
|
|
|
|
|
# Nato-chat |
|
|
|
|
|
This model was trained from scratch on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.1764 |
|
|
- Rouge1: 0.6435 |
|
|
- Rouge2: 0.5596 |
|
|
- Rougel: 0.6287 |
|
|
- Rougelsum: 0.6312 |
|
|
|
|
|
## Model description |
|
|
Flan-t5 Base |
|
|
|
|
|
### Training hyperparameters |
|
|
|
|
|
The following hyperparameters were used during training: |
|
|
- learning_rate: 2e-05 |
|
|
- train_batch_size: 16 |
|
|
- eval_batch_size: 4 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.35.2 |
|
|
- Pytorch 2.0.0 |
|
|
- Datasets 2.1.0 |
|
|
- Tokenizers 0.15.0 |
|
|
|
|
|
|
|
|
|
|
|
|
