Nahuatl_Espanol_v1 / README.md
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metadata
license: apache-2.0
base_model: google/flan-t5-base
tags:
  - generated_from_trainer
metrics:
  - bleu
model-index:
  - name: Nahuatl_Espanol_v1
    results: []

Nahuatl_Espanol_v1

This model is a fine-tuned version of google/flan-t5-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.3093
  • Bleu: 0.928
  • Gen Len: 17.3008

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
No log 0.1 100 3.4034 0.3143 17.3089
No log 0.2 200 3.1638 0.3187 17.4173
No log 0.3 300 3.0323 0.3292 17.2922
No log 0.4 400 2.9391 0.3713 17.1362
3.4051 0.5 500 2.8715 0.4182 17.2461
3.4051 0.6 600 2.8084 0.4782 17.2052
3.4051 0.71 700 2.7614 0.4541 17.1109
3.4051 0.81 800 2.7171 0.6082 17.2327
3.4051 0.91 900 2.6860 0.7904 17.2443
2.961 1.01 1000 2.6516 0.8488 17.3227
2.961 1.11 1100 2.6256 0.8094 17.3409
2.961 1.21 1200 2.5967 0.7545 17.3147
2.961 1.31 1300 2.5753 0.7891 17.2418
2.961 1.41 1400 2.5545 0.7925 17.2849
2.7764 1.51 1500 2.5335 0.7728 17.3243
2.7764 1.61 1600 2.5163 0.8055 17.4302
2.7764 1.71 1700 2.4993 0.843 17.2501
2.7764 1.81 1800 2.4840 0.8297 17.2136
2.7764 1.92 1900 2.4719 0.8457 17.3364
2.6783 2.02 2000 2.4598 0.9152 17.2453
2.6783 2.12 2100 2.4458 0.8597 17.2405
2.6783 2.22 2200 2.4345 0.8741 17.2436
2.6783 2.32 2300 2.4245 0.8681 17.3492
2.6783 2.42 2400 2.4166 0.8936 17.2708
2.6228 2.52 2500 2.4055 0.9256 17.3568
2.6228 2.62 2600 2.3960 0.9354 17.3248
2.6228 2.72 2700 2.3873 0.9543 17.3961
2.6228 2.82 2800 2.3823 0.93 17.2564
2.6228 2.92 2900 2.3740 0.9701 17.2161
2.5527 3.02 3000 2.3671 0.9669 17.26
2.5527 3.12 3100 2.3583 0.8909 17.4082
2.5527 3.23 3200 2.3555 0.9186 17.3296
2.5527 3.33 3300 2.3508 0.9321 17.3119
2.5527 3.43 3400 2.3459 0.9821 17.2859
2.5106 3.53 3500 2.3410 0.9371 17.292
2.5106 3.63 3600 2.3373 0.9368 17.2756
2.5106 3.73 3700 2.3330 0.9312 17.295
2.5106 3.83 3800 2.3304 0.9827 17.2847
2.5106 3.93 3900 2.3263 0.9637 17.2867
2.5138 4.03 4000 2.3216 0.9209 17.3356
2.5138 4.13 4100 2.3198 0.9088 17.3548
2.5138 4.23 4200 2.3177 0.9193 17.3401
2.5138 4.33 4300 2.3151 0.937 17.3346
2.5138 4.44 4400 2.3142 0.9396 17.2953
2.4804 4.54 4500 2.3130 0.9446 17.3099
2.4804 4.64 4600 2.3109 0.9449 17.3018
2.4804 4.74 4700 2.3102 0.9363 17.3106
2.4804 4.84 4800 2.3095 0.9306 17.3033
2.4804 4.94 4900 2.3093 0.928 17.3008

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2