---
license: bigscience-bloom-rail-1.0
base_model: bigscience/bloom-1b7
tags:
- generated_from_trainer
model-index:
- name: Bloom-1b7-ropes-IT-baseline
  results: []
---

<!-- 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. -->

# Bloom-1b7-ropes-IT-baseline

This model is a fine-tuned version of [bigscience/bloom-1b7](https://huggingface.co/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 ropes task here: https://huggingface.co/datasets/adambjorn/UnrelatedForgettingOverhead/viewer/ropes

## Training procedure

Given a set of prompts:

``` python
prompts = [
        "Given the following background and situation, answer the question: ",
        "Based on the background information and the current situation, what is the answer to the question? ",
        "Considering the background and the described situation, provide an answer to this question: ",
    ]
```

Each example is concatenated with the prompt, background, situation, question and answer:

``` python
input_text = f"{prompt}Background: {background} Situation: {situation} Question: {question} Answer: {answer_text}."
```


### 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': 0.024, 'grad_norm': 1.3331243991851807, 'learning_rate': 8.000000000000001e-07, 'epoch': 10.0}

Average results: {'train_runtime': 862.219, 'train_samples_per_second': 2.32, 'train_steps_per_second': 0.58, 'train_loss': 0.4160269268453121, 'epoch': 10.0}

### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2