File size: 1,407 Bytes
f1f04e7
 
33ed0e7
 
 
 
bd3b4cd
33ed0e7
 
 
f1f04e7
33ed0e7
535e416
33ed0e7
40add18
33ed0e7
 
535e416
 
 
 
 
33ed0e7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
---
license: bigscience-bloom-rail-1.0
tags:
- generated_from_trainer
datasets:
- squad_v2
base_model: bigscience/bloom-560m
model-index:
- name: debug_bloom_squad
  results: []
---

<!-- This model card has mostly been generated automatically according to the information the Trainer had access to. I've added some additional context. -->

# POC - BLOOM for QuestionAnswering, tuned on squad_v2

This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on the squad_v2 dataset.
It is intended for a proof of concept, and perhaps to serve as a starting point for others trying to do the same thing.

Ongoing discussion surrounding this effort:

https://huggingface.co/bigscience/bloom/discussions/46#633c57b2ccce04161f82e6c2 

## 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: 3e-05
- train_batch_size: 6
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.24.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.6.1
- Tokenizers 0.13.1