End of training
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- generation_config.json +6 -0
- model.safetensors +1 -1
README.md
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---
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library_name: transformers
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---
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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#### Hardware
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#### Software
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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## Model Card Contact
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[More Information Needed]
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---
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library_name: transformers
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license: apache-2.0
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base_model: t5-small
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tags:
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- generated_from_trainer
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metrics:
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- bleu
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model-index:
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- name: ft-t5-small-lg
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# ft-t5-small-lg
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the Luganda Formal Data dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2411
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- Bleu: 1.4907
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- Gen Len: 14.5428
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 30
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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| 0.3208 | 1.0 | 2051 | 0.2999 | 0.0574 | 8.6396 |
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| 0.3054 | 2.0 | 4102 | 0.2890 | 0.1846 | 8.7257 |
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| 0.2954 | 3.0 | 6153 | 0.2820 | 0.2253 | 11.5285 |
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| 0.2915 | 4.0 | 8204 | 0.2755 | 0.2485 | 11.8231 |
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| 0.2841 | 5.0 | 10255 | 0.2706 | 0.1711 | 14.2913 |
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| 0.2809 | 6.0 | 12306 | 0.2667 | 0.2453 | 14.0332 |
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| 0.2758 | 7.0 | 14357 | 0.2635 | 0.3568 | 15.1871 |
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| 0.2721 | 8.0 | 16408 | 0.2609 | 0.4433 | 15.1297 |
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| 0.2683 | 9.0 | 18459 | 0.2586 | 0.5148 | 14.9026 |
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| 0.2668 | 10.0 | 20510 | 0.2562 | 0.5717 | 14.9704 |
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| 0.2658 | 11.0 | 22561 | 0.2546 | 0.6013 | 14.9334 |
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| 0.2665 | 12.0 | 24612 | 0.2528 | 0.6211 | 14.7852 |
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| 0.2611 | 13.0 | 26663 | 0.2512 | 0.6801 | 14.7521 |
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| 0.2617 | 14.0 | 28714 | 0.2499 | 0.7704 | 14.8426 |
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| 0.2589 | 15.0 | 30765 | 0.2486 | 0.846 | 14.7227 |
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| 0.257 | 16.0 | 32816 | 0.2477 | 0.9404 | 14.6676 |
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| 0.2552 | 17.0 | 34867 | 0.2466 | 0.8846 | 14.5691 |
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| 0.2577 | 18.0 | 36918 | 0.2458 | 1.0307 | 14.6182 |
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| 0.254 | 19.0 | 38969 | 0.2450 | 1.038 | 14.5272 |
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| 0.2539 | 20.0 | 41020 | 0.2442 | 1.1301 | 14.5494 |
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| 0.2524 | 21.0 | 43071 | 0.2436 | 1.1553 | 14.571 |
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| 0.2555 | 22.0 | 45122 | 0.2429 | 1.2626 | 14.6193 |
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| 0.2506 | 23.0 | 47173 | 0.2427 | 1.3183 | 14.5 |
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| 0.2491 | 24.0 | 49224 | 0.2421 | 1.3981 | 14.5801 |
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| 0.2499 | 25.0 | 51275 | 0.2419 | 1.4025 | 14.534 |
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| 0.2482 | 26.0 | 53326 | 0.2415 | 1.404 | 14.5639 |
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| 0.2479 | 27.0 | 55377 | 0.2414 | 1.4074 | 14.554 |
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| 0.247 | 28.0 | 57428 | 0.2412 | 1.4902 | 14.542 |
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| 0.2477 | 29.0 | 59479 | 0.2411 | 1.4932 | 14.5653 |
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| 0.2477 | 30.0 | 61530 | 0.2411 | 1.4907 | 14.5428 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.0
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- Datasets 3.0.0
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- Tokenizers 0.19.1
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generation_config.json
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{
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"decoder_start_token_id": 0,
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"eos_token_id": 1,
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"pad_token_id": 0,
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"transformers_version": "4.44.2"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 242041896
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version https://git-lfs.github.com/spec/v1
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oid sha256:d4206203d307ec2b6dc82445710e052e3ed62aa340ddc14e5cf8a67071bbd545
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size 242041896
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