Model save
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README.md
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license: mit
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base_model: microsoft/deberta-v3-large
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tags:
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- generated_from_trainer
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model-index:
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# checkpoints_1_18
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This model
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- Map@3: 0.
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## Model description
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step
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| 1.2303 | 1.05 | 5000 | 1.0037 | 0.7197 |
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| 1.2128 | 1.16 | 5500 | 1.0335 | 0.7263 |
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| 1.2259 | 1.26 | 6000 | 1.0124 | 0.7190 |
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| 1.21 | 1.37 | 6500 | 1.0217 | 0.7227 |
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| 1.1958 | 1.47 | 7000 | 1.0010 | 0.7292 |
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| 1.1967 | 1.58 | 7500 | 1.0042 | 0.7245 |
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| 1.1831 | 1.68 | 8000 | 1.0252 | 0.7317 |
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| 1.2083 | 1.79 | 8500 | 1.0379 | 0.7387 |
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| 1.1986 | 1.9 | 9000 | 1.0299 | 0.7292 |
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| 1.1866 | 2.0 | 9500 | 1.0024 | 0.7308 |
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| 1.1635 | 2.11 | 10000 | 1.0086 | 0.7290 |
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| 1.1575 | 2.21 | 10500 | 1.0042 | 0.7252 |
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| 1.1674 | 2.32 | 11000 | 1.0056 | 0.7283 |
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| 1.1572 | 2.42 | 11500 | 1.0119 | 0.7260 |
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| 1.1498 | 2.53 | 12000 | 1.0074 | 0.7250 |
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| 1.1489 | 2.63 | 12500 | 1.0054 | 0.7277 |
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| 1.1478 | 2.74 | 13000 | 1.0094 | 0.7278 |
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| 1.165 | 2.84 | 13500 | 1.0080 | 0.7282 |
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| 1.1265 | 2.95 | 14000 | 1.0089 | 0.7285 |
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### Framework versions
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---
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tags:
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- generated_from_trainer
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model-index:
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# checkpoints_1_18
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This model was trained from scratch on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0012
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- Map@3: 0.7287
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## Model description
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Map@3 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 1.2427 | 0.11 | 500 | 1.0237 | 0.7212 |
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| 1.2405 | 0.21 | 1000 | 1.0134 | 0.7207 |
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| 1.2422 | 0.32 | 1500 | 1.0270 | 0.7100 |
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| 1.2396 | 0.42 | 2000 | 1.0296 | 0.7190 |
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| 1.2227 | 0.53 | 2500 | 1.0178 | 0.7227 |
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| 1.2034 | 0.63 | 3000 | 1.0097 | 0.7202 |
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| 1.2138 | 0.74 | 3500 | 1.0076 | 0.7267 |
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| 1.2082 | 0.84 | 4000 | 1.0036 | 0.7278 |
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| 1.2161 | 0.95 | 4500 | 1.0012 | 0.7287 |
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### Framework versions
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