--- library_name: transformers license: apache-2.0 base_model: google/mt5-small tags: - generated_from_trainer model-index: - name: mt5-small-gigatrue-slovak-D-5 results: [] --- # mt5-small-gigatrue-slovak-D-5 This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.3084 ## 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: 0.0003 - train_batch_size: 128 - eval_batch_size: 128 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:-----:|:---------------:| | 3.8074 | 0.1015 | 3000 | 2.4561 | | 3.182 | 0.2030 | 6000 | 2.3883 | | 3.1161 | 0.3044 | 9000 | 2.3654 | | 3.0863 | 0.4059 | 12000 | 2.3397 | | 3.0643 | 0.5074 | 15000 | 2.3349 | | 3.0593 | 0.6089 | 18000 | 2.3233 | | 3.0519 | 0.7104 | 21000 | 2.3253 | | 3.0464 | 0.8119 | 24000 | 2.3208 | | 3.0434 | 0.9133 | 27000 | 2.3229 | | 3.0389 | 1.0148 | 30000 | 2.3194 | | 3.0377 | 1.1163 | 33000 | 2.3155 | | 3.0319 | 1.2178 | 36000 | 2.3133 | | 3.0328 | 1.3193 | 39000 | 2.3104 | | 3.0314 | 1.4207 | 42000 | 2.3098 | | 3.0306 | 1.5222 | 45000 | 2.3096 | | 3.0251 | 1.6237 | 48000 | 2.3147 | | 3.027 | 1.7252 | 51000 | 2.3095 | | 3.0238 | 1.8267 | 54000 | 2.3099 | | 3.0246 | 1.9282 | 57000 | 2.3082 | | 3.0253 | 2.0296 | 60000 | 2.3076 | | 3.0261 | 2.1311 | 63000 | 2.3103 | | 3.0242 | 2.2326 | 66000 | 2.3085 | | 3.0245 | 2.3341 | 69000 | 2.3078 | | 3.024 | 2.4356 | 72000 | 2.3096 | | 3.0251 | 2.5370 | 75000 | 2.3086 | | 3.0257 | 2.6385 | 78000 | 2.3081 | | 3.0224 | 2.7400 | 81000 | 2.3088 | | 3.0267 | 2.8415 | 84000 | 2.3083 | | 3.0243 | 2.9430 | 87000 | 2.3084 | ### Framework versions - Transformers 4.45.2 - Pytorch 2.5.1 - Datasets 3.2.0 - Tokenizers 0.20.3