File size: 1,824 Bytes
c63c0f3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
---
license: bsd-3-clause
base_model: Salesforce/codegen-2B-nl
tags:
- generated_from_trainer
datasets:
- matthewdelorenzo/archgen
metrics:
- accuracy
model-index:
- name: output_llm
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: matthewdelorenzo/archgen
      type: matthewdelorenzo/archgen
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8559900076029108
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/llm_team_tamu/huggingface/runs/1za7vikx)
# output_llm

This model is a fine-tuned version of [Salesforce/codegen-2B-nl](https://huggingface.co/Salesforce/codegen-2B-nl) on the matthewdelorenzo/archgen dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6558
- Accuracy: 0.8560

## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1