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eskayML
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interview_electra

Text Classification
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electra
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eskayML/interview_electra

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  1. README.md +24 -24
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. runs/Jun18_19-56-01_0c265ed1ed29/events.out.tfevents.1718740561.0c265ed1ed29.821.1 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [mrm8488/electra-small-finetuned-squadv2](https://huggingface.co/mrm8488/electra-small-finetuned-squadv2) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3918
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- - Accuracy: 0.7261
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  ## Model description
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@@ -49,31 +49,31 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 79 | 2.2793 | 0.1720 |
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- | No log | 2.0 | 158 | 2.2569 | 0.2102 |
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- | No log | 3.0 | 237 | 2.2141 | 0.2866 |
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- | No log | 4.0 | 316 | 2.1554 | 0.3121 |
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- | No log | 5.0 | 395 | 2.0661 | 0.5096 |
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- | No log | 6.0 | 474 | 1.9949 | 0.5669 |
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- | 2.2016 | 7.0 | 553 | 1.9088 | 0.5987 |
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- | 2.2016 | 8.0 | 632 | 1.8361 | 0.5605 |
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- | 2.2016 | 9.0 | 711 | 1.7648 | 0.6306 |
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- | 2.2016 | 10.0 | 790 | 1.7013 | 0.6561 |
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- | 2.2016 | 11.0 | 869 | 1.6548 | 0.6115 |
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- | 2.2016 | 12.0 | 948 | 1.5916 | 0.6943 |
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- | 1.812 | 13.0 | 1027 | 1.5425 | 0.6943 |
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- | 1.812 | 14.0 | 1106 | 1.5137 | 0.7006 |
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- | 1.812 | 15.0 | 1185 | 1.4722 | 0.7261 |
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- | 1.812 | 16.0 | 1264 | 1.4426 | 0.7197 |
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- | 1.812 | 17.0 | 1343 | 1.4216 | 0.7197 |
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- | 1.812 | 18.0 | 1422 | 1.4061 | 0.7325 |
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- | 1.5304 | 19.0 | 1501 | 1.3961 | 0.7325 |
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- | 1.5304 | 20.0 | 1580 | 1.3918 | 0.7261 |
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  ### Framework versions
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- - Transformers 4.41.1
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  - Pytorch 2.3.0+cu121
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- - Datasets 2.19.2
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  - Tokenizers 0.19.1
 
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  This model is a fine-tuned version of [mrm8488/electra-small-finetuned-squadv2](https://huggingface.co/mrm8488/electra-small-finetuned-squadv2) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.4308
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+ - Accuracy: 0.8675
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 76 | 2.2703 | 0.1589 |
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+ | No log | 2.0 | 152 | 2.2403 | 0.1656 |
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+ | No log | 3.0 | 228 | 2.1815 | 0.3311 |
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+ | No log | 4.0 | 304 | 2.1125 | 0.4636 |
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+ | No log | 5.0 | 380 | 2.0395 | 0.4503 |
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+ | No log | 6.0 | 456 | 1.9782 | 0.5232 |
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+ | 2.1758 | 7.0 | 532 | 1.9149 | 0.4768 |
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+ | 2.1758 | 8.0 | 608 | 1.8410 | 0.5497 |
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+ | 2.1758 | 9.0 | 684 | 1.7949 | 0.5497 |
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+ | 2.1758 | 10.0 | 760 | 1.7268 | 0.6159 |
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+ | 2.1758 | 11.0 | 836 | 1.6659 | 0.6159 |
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+ | 2.1758 | 12.0 | 912 | 1.6137 | 0.6755 |
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+ | 2.1758 | 13.0 | 988 | 1.5773 | 0.7086 |
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+ | 1.8023 | 14.0 | 1064 | 1.5381 | 0.7748 |
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+ | 1.8023 | 15.0 | 1140 | 1.5067 | 0.8013 |
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+ | 1.8023 | 16.0 | 1216 | 1.4807 | 0.8344 |
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+ | 1.8023 | 17.0 | 1292 | 1.4590 | 0.8543 |
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+ | 1.8023 | 18.0 | 1368 | 1.4447 | 0.8477 |
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+ | 1.8023 | 19.0 | 1444 | 1.4338 | 0.8675 |
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+ | 1.5562 | 20.0 | 1520 | 1.4308 | 0.8675 |
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  ### Framework versions
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+ - Transformers 4.41.2
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  - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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  - Tokenizers 0.19.1
config.json CHANGED
@@ -48,7 +48,7 @@
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  "summary_type": "first",
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  "summary_use_proj": true,
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  "torch_dtype": "float32",
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- "transformers_version": "4.41.1",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 30522
 
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  "summary_type": "first",
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  "summary_use_proj": true,
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  "torch_dtype": "float32",
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+ "transformers_version": "4.41.2",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 30522
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