metadata

license: mit
tags:
  - generated_from_trainer
  - code
  - art
  - legal
  - finance
  - biology
  - chemistry
  - medical
  - music
  - climate
model-index:
  - name: bart-large-cnn-samsum-ChatGPT_v3
    results: []
datasets:
  - fka/awesome-chatgpt-prompts
  - Nerfgun3/bad_prompt
  - openai/webgpt_comparisons
  - Anthropic/hh-rlhf
  - Gustavosta/Stable-Diffusion-Prompts
  - openai/summarize_from_feedback
  - allenai/soda
  - poloclub/diffusiondb
  - Linaqruf/pixiv-niji-journey
  - allenai/objaverse
language:
  - en
metrics:
  - accuracy
  - bertscore
  - code_eval
  - bleu
  - bleurt
library_name: adapter-transformers
pipeline_tag: conversational

bart-large-cnn-samsum-ChatGPT_v3

This model is a fine-tuned version of philschmid/bart-large-cnn-samsum on an unknown dataset.

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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP

Framework versions

Transformers 4.24.0
Pytorch 1.12.1
Datasets 2.6.1
Tokenizers 0.13.2