amtibot_bart / README.md
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metadata
license: mit
base_model: facebook/bart-large-cnn
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: amtibot_bart
    results: []
library_name: peft

amtibot_bart

This model is a fine-tuned version of facebook/bart-large-cnn on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5905
  • Rouge1: 0.4051
  • Rouge2: 0.195
  • Rougel: 0.3054
  • Rougelsum: 0.3053
  • Gen Len: 65.7532

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: 0.02
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 0.9351 9 1.6594 0.4057 0.1833 0.3052 0.3048 67.9481
2.11 1.9740 19 1.6149 0.3938 0.192 0.3063 0.3058 64.8571
1.554 2.9091 28 1.5842 0.3956 0.1872 0.3039 0.3033 65.8182
1.3821 3.7403 36 1.5905 0.4051 0.195 0.3054 0.3053 65.7532

Framework versions

  • PEFT 0.4.0
  • Transformers 4.40.1
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.19.1