H-Z-Ning
/

Senti-RoBERTa-Mini

Text Classification

sentiment-analysis

text-embeddings-inference

Model card Files Files and versions

H-Z-Ning commited on Aug 29, 2025

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0d23886

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1 Parent(s): 349b43c

Update README.md

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@@ -73,8 +73,8 @@ print("predicted rating:", pred)
 |---|---|
 | Base model | hfl/chinese-roberta-wwm-ext |
 | Training framework | 🤗 transformers `Trainer` |
-| Training set | 50 000 samples (randomly drawn from 2000 K) |
-| Validation set | 5 000 samples (same random draw) |
 | Test set | full original test set |
 | Max sequence length | 256 |
 | Training epochs | 3 |
@@ -85,7 +85,7 @@ print("predicted rating:", pred)
 | Scheduler | linear warmup (warmup_ratio=0.1) |
 | Precision | FP16 |
 | Best-model criterion | **QWK (↑)** |
-| Training time | ≈ 32 min on single P100 (FP16) |
 | Logging interval | every 10 steps |
 ---

 |---|---|
 | Base model | hfl/chinese-roberta-wwm-ext |
 | Training framework | 🤗 transformers `Trainer` |
+| Training set | 150 000 samples (randomly drawn from 2000 K) |
+| Validation set | 15 000 samples (same random draw) |
 | Test set | full original test set |
 | Max sequence length | 256 |
 | Training epochs | 3 |
 | Scheduler | linear warmup (warmup_ratio=0.1) |
 | Precision | FP16 |
 | Best-model criterion | **QWK (↑)** |
+| Training time | ≈ 120 min on single P100 (FP16) |
 | Logging interval | every 10 steps |
 ---