# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("datnth1709/VietAI-NLP-ITN")
model = AutoModelForSeq2SeqLM.from_pretrained("datnth1709/VietAI-NLP-ITN", device_map="auto")Quick Links
VietAI-NLP-ITN
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4378
- Bleu: 81.8571
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 0.6529 | 1.0 | 31250 | 0.5660 | 78.7315 |
| 0.5125 | 2.0 | 62500 | 0.4770 | 81.3979 |
| 0.4798 | 3.0 | 93750 | 0.4554 | 81.6720 |
| 0.4568 | 4.0 | 125000 | 0.4435 | 81.7753 |
| 0.4387 | 5.0 | 156250 | 0.4378 | 81.8571 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="datnth1709/VietAI-NLP-ITN")