File size: 1,450 Bytes
85306fb 6d3e9e8 85306fb 6d3e9e8 85306fb 6d3e9e8 85306fb 6d3e9e8 85306fb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 |
---
language:
- en
- ro
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- Lvxue/wmt16
metrics:
- bleu
model-index:
- name: distilled-mt5-base-pseudo-labeling
results:
- task:
name: Translation
type: translation
dataset:
name: Lvxue/wmt16 ro-en
type: Lvxue/wmt16
args: ro-en
metrics:
- name: Bleu
type: bleu
value: 24.1355
---
<!-- 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. -->
# distilled-mt5-base-pseudo-labeling
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the Lvxue/wmt16 ro-en dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6487
- Bleu: 24.1355
- Gen Len: 44.1211
## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
### Training results
### Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
|