metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- Fraser/short-jokes
metrics:
- accuracy
model-index:
- name: pythia-1.4b-deduped-jokes
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: Fraser/short-jokes
type: Fraser/short-jokes
config: default
split: train[:5%]
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.986989308918276
pythia-1.4b-deduped-jokes
This model is a fine-tuned version of EleutherAI/pythia-1.4b-deduped on the Fraser/short-jokes dataset. It achieves the following results on the evaluation set:
- Loss: 0.0699
- Accuracy: 0.9870
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 400
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.06 | 100 | 0.0729 | 0.9866 |
| No log | 0.12 | 200 | 0.0716 | 0.9868 |
| No log | 0.17 | 300 | 0.0705 | 0.9869 |
| No log | 0.23 | 400 | 0.0699 | 0.9870 |
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 2.0.0-rc1
- Datasets 2.11.0
- Tokenizers 0.13.3