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---
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: BERT2BERT_finetuned
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# BERT2BERT_finetuned
This model is a fine-tuned version of [JulienRPA/BERT2BERT_pretrained_LC-QuAD_2.0](https://huggingface.co/JulienRPA/BERT2BERT_pretrained_LC-QuAD_2.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1672
- Bleu: 96.7679
- Em: 0.6307
- Rm: 0.7482
- Gen Len: 75.6355
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 300.0
### Training results
| Training Loss | Epoch | Step | Bleu | Em | Gen Len | Validation Loss | Rm |
|:-------------:|:------:|:-----:|:-------:|:------:|:-------:|:---------------:|:------:|
| 3.4354 | 12.82 | 500 | 56.6427 | 0.0 | 70.5947 | 1.5065 | 0.0 |
| 0.8473 | 25.64 | 1000 | 90.5419 | 0.0192 | 76.9736 | 0.3859 | 0.0216 |
| 0.2049 | 38.46 | 1500 | 93.6495 | 0.0504 | 75.1655 | 0.2472 | 0.0671 |
| 0.1222 | 51.28 | 2000 | 93.8388 | 0.0959 | 75.6403 | 0.2338 | 0.1487 |
| 0.0923 | 64.1 | 2500 | 94.71 | 0.2158 | 75.8177 | 0.1944 | 0.2662 |
| 0.0752 | 76.92 | 3000 | 95.0458 | 0.2662 | 75.2638 | 0.1990 | 0.3022 |
| 0.0627 | 89.74 | 3500 | 95.3518 | 0.3429 | 76.9928 | 0.1957 | 0.3957 |
| 0.052 | 102.56 | 4000 | 95.5392 | 0.3837 | 76.1007 | 0.1861 | 0.4508 |
| 0.0457 | 115.38 | 4500 | 95.6692 | 0.4173 | 76.1727 | 0.1880 | 0.4892 |
| 0.0386 | 128.21 | 5000 | 95.9215 | 0.446 | 76.0168 | 0.1850 | 0.5276 |
| 0.0321 | 141.03 | 5500 | 95.931 | 0.4964 | 75.2566 | 0.1724 | 0.5875 |
| 0.026 | 153.85 | 6000 | 96.4317 | 0.5348 | 75.741 | 0.1687 | 0.6499 |
| 0.0242 | 166.67 | 6500 | 96.197 | 0.5372 | 76.1127 | 0.1707 | 0.6403 |
| 0.0193 | 179.49 | 7000 | 96.3422 | 0.5564 | 75.3933 | 0.1643 | 0.6691 |
| 0.0164 | 192.31 | 7500 | 96.5278 | 0.5779 | 75.4508 | 0.1650 | 0.693 |
| 0.0139 | 205.13 | 8000 | 96.6382 | 0.6091 | 75.9592 | 0.1668 | 0.7314 |
| 0.012 | 217.95 | 8500 | 96.5488 | 0.6163 | 76.0024 | 0.1644 | 0.729 |
| 0.0106 | 230.77 | 9000 | 96.6353 | 0.6091 | 75.5468 | 0.1653 | 0.7266 |
| 0.0093 | 243.59 | 9500 | 96.8984 | 0.6331 | 75.7242 | 0.1663 | 0.7482 |
| 0.0084 | 256.41 | 10000 | 96.6199 | 0.6331 | 75.3885 | 0.1676 | 0.7482 |
| 0.0076 | 269.23 | 10500 | 0.1678 | 96.5038| 0.6283 | 0.7482 | 75.3453|
| 0.007 | 282.05 | 11000 | 0.1669 | 96.7187| 0.6355 | 0.7458 | 75.9281|
| 0.0065 | 294.87 | 11500 | 0.1672 | 96.7679| 0.6307 | 0.7482 | 75.6355|
### Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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