Instructions to use RoeiG/laya-hebrew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Laya
How to use RoeiG/laya-hebrew with Laya:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Card: drop an unverified claim
Browse files
README.md
CHANGED
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@@ -157,7 +157,7 @@ Differences smaller than these are noise. This checkpoint is seed 1, which was f
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- Strong keywords in the text can outweigh the option descriptions.
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- **Claim-form relevance is slightly below the previous checkpoint:** he_bench 0.78 against 0.80, and BEIR-he 0.78 against 0.82.
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- **Scales:** sentiment and tone are about 0.45 accuracy, and the tone probabilities are overconfident (valence Brier
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0.53).
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- **Calculated fields steer less than in the previous checkpoint.** On 8 test emails, a "direct manager" sender field
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raised importance by 0.11 of a level, against 0.22 before, and a "mailing list" field lowered it in only 2 of 8.
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- **Calibration does not catch everything.** The failures above are often high-confidence, so a confidence threshold
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@@ -165,8 +165,8 @@ Differences smaller than these are noise. This checkpoint is seed 1, which was f
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## Training data
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The training start was an earlier checkpoint of this project,
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encoder and 1e-4 for the head. Every case was converted to Laya's format, with a random subset of options, paraphrased
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instructions and varied field names.
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| 157 |
- Strong keywords in the text can outweigh the option descriptions.
|
| 158 |
- **Claim-form relevance is slightly below the previous checkpoint:** he_bench 0.78 against 0.80, and BEIR-he 0.78 against 0.82.
|
| 159 |
- **Scales:** sentiment and tone are about 0.45 accuracy, and the tone probabilities are overconfident (valence Brier
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| 160 |
+
0.53).
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| 161 |
- **Calculated fields steer less than in the previous checkpoint.** On 8 test emails, a "direct manager" sender field
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| 162 |
raised importance by 0.11 of a level, against 0.22 before, and a "mailing list" field lowered it in only 2 of 8.
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| 163 |
- **Calibration does not catch everything.** The failures above are often high-confidence, so a confidence threshold
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## Training data
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The training start was an earlier checkpoint of this project, with the same encoder, trained on part of the public
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data below. The run was one epoch over 396,508 items (6,196 updates, 1.4 A100 hours). The learning rates were 5e-6 for the
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encoder and 1e-4 for the head. Every case was converted to Laya's format, with a random subset of options, paraphrased
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| 171 |
instructions and varied field names.
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| 172 |
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