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:

python

# 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

alonzogarbanzo/Bloom-1b7-winograd-wsc-IT-baseline

Bloom-1b7-winograd-wsc-IT-baseline

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

alonzogarbanzo/
Bloom-1b7-winograd-wsc-IT-baseline