Text Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
sagemaker
bertin
TextClassification
SentimentAnalysis
Eval Results (legacy)
text-embeddings-inference
Instructions to use edumunozsala/bertin_base_sentiment_analysis_es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edumunozsala/bertin_base_sentiment_analysis_es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="edumunozsala/bertin_base_sentiment_analysis_es")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("edumunozsala/bertin_base_sentiment_analysis_es") model = AutoModelForSequenceClassification.from_pretrained("edumunozsala/bertin_base_sentiment_analysis_es") - Notebooks
- Google Colab
- Kaggle
Commit ·
a9d7491
1
Parent(s): daaee21
commit files to HF hub
Browse files- eval_results.txt +12 -0
- output.tar.gz +0 -3
eval_results.txt
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epoch = 5.0
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eval_accuracy = 0.8989333333333334
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eval_f1 = 0.8989063750333421
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eval_loss = 0.36687323451042175
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eval_mem_cpu_alloc_delta = 0
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eval_mem_cpu_peaked_delta = 0
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eval_mem_gpu_alloc_delta = 0
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eval_mem_gpu_peaked_delta = 95293952
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eval_precision = 0.877147319104633
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eval_recall = 0.9217724288840262
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eval_runtime = 115.9432
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eval_samples_per_second = 32.343
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output.tar.gz
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version https://git-lfs.github.com/spec/v1
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oid sha256:00c8a48963798a3b51766df66a882ebc64bfd53aacdba529bd2791771c0c9c89
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size 303
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