# Load model directly
from transformers import AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("gowitheflowlab/parallel-major-languages-from-allnli", dtype="auto")Quick Links
allnli_wikispan_unsup_ensemble_last**-64-128-3e-5-9400
This model is a fine-tuned version of zxh4546/allnli_wikispan_unsup_ensemble_last on the PARALLEL-PT-NL-PL dataset.
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: 3e-05
- train_batch_size: 128
- 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_steps: 1000
- training_steps: 9400
Training results
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0
- Datasets 2.14.6
- Tokenizers 0.15.0
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gowitheflowlab/parallel-major-languages-from-allnli")