TRBLLmaker -- Transformer Reads Between Lyrics Lines maker
Paper • 2212.04917 • Published
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("tokeron/TRBLLmaker")
model = AutoModelForCausalLM.from_pretrained("tokeron/TRBLLmaker")Quick Links
About Us
Created by Mor Ventura and Michael Toker.
tags: - generated_from_trainer metrics: - accuracy model-index: - name: checkpoint_gpt2-medium_lyrics_meaning_2022-03-10-16-16-32 results: []
checkpoint_gpt2-medium_lyrics_meaning_2022-03-10-16-16-32
This model is a fine-tuned version of gpt2-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5896
- Accuracy: 0.4923
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.7781 | 1.01 | 128 | 2.6284 | 0.4875 |
| 2.6217 | 2.02 | 256 | 2.6022 | 0.4908 |
| 2.569 | 3.02 | 384 | 2.5928 | 0.4917 |
Framework versions
- Transformers 4.18.0.dev0
- Pytorch 1.10.1
- Datasets 1.18.3
- Tokenizers 0.11.6
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tokeron/TRBLLmaker")