seq2seq_imlla / README.md
Aleksandra Baranowska
Add model, config, tokenizer, and custom code
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---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- iva_mt_wslot
metrics:
- bleu
model-index:
- name: seq2seq_imlla
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. -->
# seq2seq_imlla
This model is a fine-tuned version of [](https://huggingface.co/) on the iva_mt_wslot dataset.
It achieves the following results on the evaluation set:
- Loss: 6.0658
- Bleu: 0.0042
- Gen Len: 5.8248
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:------:|:-------:|
| 7.441 | 0.9992 | 636 | 7.0735 | 0.0 | 5.3206 |
| 6.5312 | 2.0 | 1273 | 6.4544 | 0.0175 | 9.5238 |
| 6.0704 | 2.9992 | 1909 | 6.2110 | 0.0007 | 4.9967 |
| 5.8907 | 4.0 | 2546 | 6.1000 | 0.0055 | 6.944 |
| 5.7606 | 4.9961 | 3180 | 6.0658 | 0.0042 | 5.8248 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3