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Muhammad7777
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all-MiniLM-L6-v2-twitter-sentiment

Text Classification
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Safetensors
bert
Generated from Trainer
text-embeddings-inference
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Muhammad7777 commited on
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Files changed (6) hide show
  1. README.md +46 -18
  2. all_results.json +9 -9
  3. logs/events.out.tfevents.1756830442.fa13a7fc373e.960.2 +2 -2
  4. logs/events.out.tfevents.1756831049.fa13a7fc373e.960.3 +3 -0
  5. model.safetensors +1 -1
  6. test_results.json +9 -9
README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6688
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- - Accuracy: 0.6958
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- - F1: 0.6951
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- - Precision: 0.6989
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- - Recall: 0.6958
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  ## Model description
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@@ -51,7 +51,7 @@ The following hyperparameters were used during training:
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 500
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- - num_epochs: 1
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  - mixed_precision_training: Native AMP
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  ### Training results
@@ -60,18 +60,46 @@ The following hyperparameters were used during training:
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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  | 1.0307 | 0.0702 | 200 | 1.0141 | 0.435 | 0.2643 | 0.5984 | 0.435 |
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  | 0.8189 | 0.1403 | 400 | 0.7692 | 0.6685 | 0.6557 | 0.6946 | 0.6685 |
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- | 0.7455 | 0.2105 | 600 | 0.7126 | 0.686 | 0.6833 | 0.6829 | 0.686 |
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- | 0.7116 | 0.2806 | 800 | 0.6831 | 0.7055 | 0.7049 | 0.7119 | 0.7055 |
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- | 0.6893 | 0.3508 | 1000 | 0.6729 | 0.7075 | 0.7066 | 0.7091 | 0.7075 |
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- | 0.6707 | 0.4209 | 1200 | 0.6567 | 0.7 | 0.7015 | 0.7042 | 0.7 |
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- | 0.695 | 0.4911 | 1400 | 0.6514 | 0.7095 | 0.7107 | 0.7126 | 0.7095 |
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- | 0.6875 | 0.5612 | 1600 | 0.6461 | 0.7065 | 0.7069 | 0.7078 | 0.7065 |
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- | 0.6784 | 0.6314 | 1800 | 0.6415 | 0.7165 | 0.7176 | 0.7194 | 0.7165 |
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- | 0.6995 | 0.7015 | 2000 | 0.6496 | 0.7095 | 0.7072 | 0.7123 | 0.7095 |
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- | 0.6476 | 0.7717 | 2200 | 0.6365 | 0.7165 | 0.7182 | 0.7217 | 0.7165 |
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- | 0.6471 | 0.8418 | 2400 | 0.6335 | 0.726 | 0.7267 | 0.7276 | 0.726 |
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- | 0.6551 | 0.9120 | 2600 | 0.6333 | 0.7235 | 0.7250 | 0.7279 | 0.7235 |
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- | 0.6292 | 0.9821 | 2800 | 0.6323 | 0.7215 | 0.7213 | 0.7215 | 0.7215 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) on an unknown dataset.
23
  It achieves the following results on the evaluation set:
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+ - Loss: 0.7018
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+ - Accuracy: 0.6891
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+ - F1: 0.6879
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+ - Precision: 0.6940
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+ - Recall: 0.6891
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  ## Model description
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 3
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  - mixed_precision_training: Native AMP
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  ### Training results
 
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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  | 1.0307 | 0.0702 | 200 | 1.0141 | 0.435 | 0.2643 | 0.5984 | 0.435 |
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  | 0.8189 | 0.1403 | 400 | 0.7692 | 0.6685 | 0.6557 | 0.6946 | 0.6685 |
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+ | 0.746 | 0.2105 | 600 | 0.7140 | 0.6845 | 0.6814 | 0.6812 | 0.6845 |
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+ | 0.7113 | 0.2806 | 800 | 0.6845 | 0.701 | 0.7003 | 0.7108 | 0.701 |
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+ | 0.6897 | 0.3508 | 1000 | 0.6715 | 0.703 | 0.7023 | 0.7058 | 0.703 |
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+ | 0.6705 | 0.4209 | 1200 | 0.6571 | 0.7 | 0.7017 | 0.7046 | 0.7 |
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+ | 0.6948 | 0.4911 | 1400 | 0.6541 | 0.7 | 0.7024 | 0.7090 | 0.7 |
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+ | 0.6926 | 0.5612 | 1600 | 0.6452 | 0.7115 | 0.7121 | 0.7138 | 0.7115 |
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+ | 0.6763 | 0.6314 | 1800 | 0.6394 | 0.719 | 0.7200 | 0.7216 | 0.719 |
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+ | 0.6997 | 0.7015 | 2000 | 0.6698 | 0.6935 | 0.6858 | 0.7050 | 0.6935 |
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+ | 0.6465 | 0.7717 | 2200 | 0.6327 | 0.716 | 0.7167 | 0.7181 | 0.716 |
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+ | 0.6478 | 0.8418 | 2400 | 0.6339 | 0.7265 | 0.7277 | 0.7301 | 0.7265 |
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+ | 0.6534 | 0.9120 | 2600 | 0.6447 | 0.7175 | 0.7191 | 0.7271 | 0.7175 |
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+ | 0.6408 | 0.9821 | 2800 | 0.6184 | 0.725 | 0.7245 | 0.7241 | 0.725 |
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+ | 0.5421 | 1.0523 | 3000 | 0.6390 | 0.7145 | 0.7166 | 0.7216 | 0.7145 |
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+ | 0.5701 | 1.1224 | 3200 | 0.6339 | 0.725 | 0.7242 | 0.7242 | 0.725 |
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+ | 0.5974 | 1.1926 | 3400 | 0.6308 | 0.725 | 0.7238 | 0.7237 | 0.725 |
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+ | 0.5872 | 1.2627 | 3600 | 0.6252 | 0.726 | 0.7272 | 0.7299 | 0.726 |
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+ | 0.5847 | 1.3329 | 3800 | 0.6265 | 0.7315 | 0.7329 | 0.7359 | 0.7315 |
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+ | 0.5906 | 1.4030 | 4000 | 0.6354 | 0.7205 | 0.7198 | 0.7244 | 0.7205 |
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+ | 0.5541 | 1.4732 | 4200 | 0.6206 | 0.7305 | 0.7309 | 0.7314 | 0.7305 |
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+ | 0.5922 | 1.5433 | 4400 | 0.6214 | 0.7305 | 0.7314 | 0.7334 | 0.7305 |
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+ | 0.5816 | 1.6135 | 4600 | 0.6329 | 0.7275 | 0.7290 | 0.7358 | 0.7275 |
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+ | 0.5312 | 1.6836 | 4800 | 0.6438 | 0.719 | 0.7170 | 0.7223 | 0.719 |
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+ | 0.5477 | 1.7538 | 5000 | 0.6297 | 0.727 | 0.7269 | 0.7292 | 0.727 |
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+ | 0.5488 | 1.8239 | 5200 | 0.6314 | 0.7295 | 0.7290 | 0.7292 | 0.7295 |
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+ | 0.5541 | 1.8941 | 5400 | 0.6186 | 0.734 | 0.7340 | 0.7342 | 0.734 |
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+ | 0.587 | 1.9642 | 5600 | 0.6103 | 0.734 | 0.7338 | 0.7340 | 0.734 |
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+ | 0.5011 | 2.0344 | 5800 | 0.6428 | 0.729 | 0.7303 | 0.7362 | 0.729 |
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+ | 0.5241 | 2.1045 | 6000 | 0.6288 | 0.7315 | 0.7322 | 0.7331 | 0.7315 |
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+ | 0.5462 | 2.1747 | 6200 | 0.6369 | 0.728 | 0.7251 | 0.7263 | 0.728 |
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+ | 0.4792 | 2.2448 | 6400 | 0.6365 | 0.729 | 0.7306 | 0.7339 | 0.729 |
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+ | 0.5222 | 2.3150 | 6600 | 0.6320 | 0.73 | 0.7295 | 0.7292 | 0.73 |
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+ | 0.4967 | 2.3851 | 6800 | 0.6326 | 0.729 | 0.7288 | 0.7296 | 0.729 |
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+ | 0.5261 | 2.4553 | 7000 | 0.6316 | 0.726 | 0.7250 | 0.7246 | 0.726 |
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+ | 0.519 | 2.5254 | 7200 | 0.6329 | 0.7285 | 0.7293 | 0.7307 | 0.7285 |
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+ | 0.5168 | 2.5956 | 7400 | 0.6279 | 0.7315 | 0.7324 | 0.7343 | 0.7315 |
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+ | 0.4944 | 2.6657 | 7600 | 0.6308 | 0.7325 | 0.7322 | 0.7321 | 0.7325 |
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+ | 0.5048 | 2.7359 | 7800 | 0.6424 | 0.73 | 0.7306 | 0.7322 | 0.73 |
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+ | 0.5201 | 2.8060 | 8000 | 0.6342 | 0.734 | 0.7343 | 0.7349 | 0.734 |
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+ | 0.5391 | 2.8762 | 8200 | 0.6314 | 0.7305 | 0.7307 | 0.7311 | 0.7305 |
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+ | 0.5361 | 2.9463 | 8400 | 0.6353 | 0.733 | 0.7335 | 0.7342 | 0.733 |
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  ### Framework versions
all_results.json CHANGED
@@ -1,11 +1,11 @@
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- "eval_runtime": 6.7278,
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- "eval_samples_per_second": 1825.854,
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- "eval_steps_per_second": 28.538
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