8dd8934fb108f95a911b5e26447ebb59
This model is a fine-tuned version of google/umt5-base on the Helsinki-NLP/opus_books [es-it] dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4803
- Data Size: 1.0
- Epoch Runtime: 166.0883
- Bleu: 5.5138
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
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_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: constant
- num_epochs: 50
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Data Size |
Epoch Runtime |
Bleu |
| No log |
0 |
0 |
11.8845 |
0 |
13.7090 |
0.2804 |
| No log |
1 |
721 |
11.6500 |
0.0078 |
16.0695 |
0.2535 |
| No log |
2 |
1442 |
11.2228 |
0.0156 |
17.5692 |
0.2833 |
| 0.3237 |
3 |
2163 |
10.3332 |
0.0312 |
21.3931 |
0.2913 |
| 1.0012 |
4 |
2884 |
8.5047 |
0.0625 |
26.5733 |
0.3455 |
| 8.5143 |
5 |
3605 |
4.9032 |
0.125 |
36.3316 |
1.2113 |
| 4.7327 |
6 |
4326 |
3.3371 |
0.25 |
53.9259 |
2.4238 |
| 3.8862 |
7 |
5047 |
3.0048 |
0.5 |
92.5966 |
3.2504 |
| 3.496 |
8.0 |
5768 |
2.8315 |
1.0 |
167.7369 |
3.7882 |
| 3.2634 |
9.0 |
6489 |
2.7450 |
1.0 |
167.3899 |
4.1156 |
| 3.1612 |
10.0 |
7210 |
2.6941 |
1.0 |
169.2978 |
4.3139 |
| 3.0244 |
11.0 |
7931 |
2.6593 |
1.0 |
167.3909 |
4.4523 |
| 2.9753 |
12.0 |
8652 |
2.6200 |
1.0 |
167.1947 |
4.6066 |
| 2.9187 |
13.0 |
9373 |
2.6001 |
1.0 |
167.9997 |
4.7045 |
| 2.8032 |
14.0 |
10094 |
2.5692 |
1.0 |
166.7811 |
4.8149 |
| 2.7953 |
15.0 |
10815 |
2.5495 |
1.0 |
167.2644 |
4.8632 |
| 2.7074 |
16.0 |
11536 |
2.5413 |
1.0 |
171.8496 |
4.9945 |
| 2.6703 |
17.0 |
12257 |
2.5240 |
1.0 |
169.8680 |
5.0501 |
| 2.647 |
18.0 |
12978 |
2.5165 |
1.0 |
168.5366 |
5.1315 |
| 2.587 |
19.0 |
13699 |
2.5175 |
1.0 |
168.9415 |
5.1387 |
| 2.5565 |
20.0 |
14420 |
2.4971 |
1.0 |
168.2197 |
5.2374 |
| 2.5245 |
21.0 |
15141 |
2.4939 |
1.0 |
167.6366 |
5.2264 |
| 2.4804 |
22.0 |
15862 |
2.4823 |
1.0 |
167.6528 |
5.2776 |
| 2.3955 |
23.0 |
16583 |
2.4925 |
1.0 |
170.3214 |
5.3348 |
| 2.3861 |
24.0 |
17304 |
2.4809 |
1.0 |
169.3975 |
5.3402 |
| 2.3862 |
25.0 |
18025 |
2.4828 |
1.0 |
168.1509 |
5.3585 |
| 2.3627 |
26.0 |
18746 |
2.4789 |
1.0 |
167.9541 |
5.4241 |
| 2.3147 |
27.0 |
19467 |
2.4747 |
1.0 |
168.6779 |
5.4486 |
| 2.2717 |
28.0 |
20188 |
2.4815 |
1.0 |
169.7344 |
5.4859 |
| 2.2451 |
29.0 |
20909 |
2.4765 |
1.0 |
168.6457 |
5.4487 |
| 2.2161 |
30.0 |
21630 |
2.4774 |
1.0 |
166.5616 |
5.5141 |
| 2.2003 |
31.0 |
22351 |
2.4803 |
1.0 |
166.0883 |
5.5138 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.22.1
