metadata
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 :-
bloom-560m-finetuned-the-stack-prolog
This model is a fine-tuned version of 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