Bloom-1b7-winograd-wsc-IT-baseline
This model is a fine-tuned version of bigscience/bloom-1b7 on an unknown dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
Instruction Tuned on the winograd-wsc task here: https://huggingface.co/datasets/adambjorn/UnrelatedForgettingOverhead/viewer/winograd_wsc
Training procedure
Given some prompts:
prompts = [
"Determine which option the pronoun refers to in this text: ",
"Given the text, identify the referent of the pronoun among these options: ",
"Read the text and decide which option is referred to by the pronoun: ",
"In the text below, to whom or what does the pronoun refer? Choose from the options: ",
]
Each example is concatenated with the prompt, text, pronoun, quote, options and correct option like so:
# Concatenate the selected prompt, text, pronoun, quote, options, and the correct option into a single string
input_text = f"{prompt}Text: '{text}' Pronoun: '{pronoun}', Quote: '{quote}'. {options_text}. {correct_option}. </s> "
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Final results: {'loss': 0.0983, 'grad_norm': 4.820842266082764, 'learning_rate': 6.000000000000001e-07, 'epoch': 10.0}
Average results: {'train_runtime': 452.2725, 'train_samples_per_second': 4.422, 'train_steps_per_second': 1.106, 'train_loss': 0.33704672479629516, 'epoch': 10.0}
Framework versions
- Transformers 4.38.1
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2