Instructions to use HiAmNear/cafebert-ViFE-task-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiAmNear/cafebert-ViFE-task-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HiAmNear/cafebert-ViFE-task-1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HiAmNear/cafebert-ViFE-task-1") model = AutoModelForSequenceClassification.from_pretrained("HiAmNear/cafebert-ViFE-task-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 5, checkpoint
Browse files
last-checkpoint/model.safetensors
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last-checkpoint/optimizer.pt
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last-checkpoint/rng_state.pth
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last-checkpoint/scheduler.pt
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last-checkpoint/trainer_state.json
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"step": 195
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"logging_steps": 500,
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"attributes": {}
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"best_metric": 0.8298722044728435,
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"best_model_checkpoint": "../../modelParams/TrainingArguments_output/checkpoint-234",
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"epoch": 5.980830670926517,
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"eval_samples_per_second": 37.761,
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{
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"eval_accuracy": 0.8298722044728435,
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"eval_runtime": 33.1468,
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"eval_samples_per_second": 37.771,
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"eval_steps_per_second": 4.737,
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"step": 234
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"logging_steps": 500,
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"attributes": {}
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"total_flos": 1.394390632110174e+16,
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"train_batch_size": 8,
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