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cartesinus/iva_mt_wslot-m2m100_418M-en-es-massive_unfiltered

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Downloads · 30-day
9
↑ 600% in 90 days
Likes
0
Model age
3.5y ago
created 2023-04-26

Training datasets

Corpora the author lists in the model card. Datasets tracked in our /datasets catalog carry a category badge linking to the workflow stage. Others open on Hugging Face.

Downloads over time
Now35→from5↑600%
049981465 on Jul 24, 202435 on Oct 11133 on Sep 17, 2025Jul '24Nov '24Mar '25Jul '25Nov '25MarJul
Jul 24, 2024 → Oct 11 · 155 snapshots · spans 809 days

Metadata

License
mit
Tags
transformers pytorch tensorboard m2m_100 text2text-generation generated_from_trainer dataset:iva_mt_wslot-exp license:mit model-index endpoints_compatible region:us
Total size
1.81 GB
Files
11
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2023-04-27 01:25

Files by quantization

Auxiliary files 11 files 1.82 GB
pytorch_model.bin 1.81 GB 704c0c5f download
training_args.bin 3.75 KB 49751ad7 download
vocab.json 3.54 MB 380e263b download
sentencepiece.bpe.model 2.31 MB d8f7c76e download
README.md 2.18 KB 42061397 download
tokenizer_config.json 1.77 KB cf4842df download
special_tokens_map.json 1.52 KB 57f8d155 download
.gitattributes 1.44 KB c7d9f333 download
config.json 931 B 8e9d8948 download
generation_config.json 198 B 36b60cec download
.gitignore 13.0 B 0348ea97 download

README current version from Hugging Face


license: mit
tags:

  • generated_from_trainer
    datasets:
  • iva_mt_wslot-exp
    metrics:
  • bleu
    model-index:
  • name: iva_mt_wslot-m2m100_418M-en-es-massive_unfiltered
    results:
    • task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
      dataset:
      name: iva_mt_wslot-exp
      type: iva_mt_wslot-exp
      config: en-es
      split: validation
      args: en-es
      metrics:
      • name: Bleu
        type: bleu
        value: 67.6426

iva_mt_wslot-m2m100_418M-en-es-massive_unfiltered

This model is a fine-tuned version of facebook/m2m100_418M on the iva_mt_wslot-exp dataset.
It achieves the following results on the evaluation set:

  • Loss: 0.0114
  • Bleu: 67.6426
  • Gen Len: 18.9134

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: 2e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 7
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
0.0129 1.0 2879 0.0118 65.4383 18.8697
0.009 2.0 5758 0.0109 66.6878 18.9331
0.0066 3.0 8637 0.0107 66.6143 18.8687
0.0049 4.0 11516 0.0108 66.9832 18.8067
0.0037 5.0 14395 0.0109 67.452 18.8598
0.0028 6.0 17274 0.0112 67.4281 18.9213
0.0023 7.0 20153 0.0114 67.6426 18.9134

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.3

README history 1 version

The author's README evolved over time. Click a version to see its content at that point.

  1. 2023-04-27update model card README.mdcb58fad2.2 KB
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