# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("anarodrdi/opus-suicidio-es-en")
model = AutoModelForSeq2SeqLM.from_pretrained("anarodrdi/opus-suicidio-es-en", device_map="auto")Quick Links
opus-suicidio-es-en
This model is a fine-tuned version of Helsinki-NLP/opus-mt-es-en on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.1657
- Bleu: 18.0252
- Gen Len: 37.0
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: 5.6e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 11 | 4.3934 | 17.8966 | 36.8182 |
| No log | 2.0 | 22 | 4.1657 | 18.0252 | 37.0 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
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Model tree for anarodrdi/opus-suicidio-es-en
Base model
Helsinki-NLP/opus-mt-es-en
# 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="anarodrdi/opus-suicidio-es-en")