File size: 2,142 Bytes
3eb3819 2013a93 2564a9c 3eb3819 |
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 76 77 78 79 |
---
license: bigscience-bloom-rail-1.0
tags:
- generated_from_trainer
model-index:
- name: bloom-560m-finetuned-the-stack-prolog
results: []
widget:
- text: '% Define un hecho que indica que "hello" es un saludo
saludo("hello").
% Define una regla que indica que "world" es un objeto
objeto("world").
% Define una regla que combina el saludo y el objeto para producir la salida "Hola mundo"
hola_mundo :-'
---
<!-- 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-560m-finetuned-the-stack-prolog
This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2433
## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 2
- 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: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2334 | 0.2 | 200 | 0.9993 |
| 0.9174 | 0.4 | 400 | 0.7460 |
| 0.7892 | 0.6 | 600 | 0.6046 |
| 0.6805 | 0.8 | 800 | 0.4964 |
| 0.5898 | 0.99 | 1000 | 0.4283 |
| 0.411 | 1.19 | 1200 | 0.3721 |
| 0.3705 | 1.39 | 1400 | 0.3182 |
| 0.3516 | 1.59 | 1600 | 0.2795 |
| 0.3298 | 1.79 | 1800 | 0.2528 |
| 0.2721 | 1.99 | 2000 | 0.2433 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.5.1
- Tokenizers 0.13.0
|