Training in progress, step 500, checkpoint
Browse files- checkpoint-500/README.md +219 -0
- checkpoint-500/adapter_config.json +22 -0
- checkpoint-500/adapter_model.bin +3 -0
- checkpoint-500/optimizer.pt +3 -0
- checkpoint-500/rng_state.pth +3 -0
- checkpoint-500/scheduler.pt +3 -0
- checkpoint-500/special_tokens_map.json +7 -0
- checkpoint-500/tokenizer.json +3 -0
- checkpoint-500/tokenizer_config.json +45 -0
- checkpoint-500/trainer_state.json +175 -0
- checkpoint-500/training_args.bin +3 -0
checkpoint-500/README.md
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---
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library_name: peft
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base_model: vietcuna-3b-v2/kalapa-vietcuna-3b/
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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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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<!-- This should link to a Data Card if possible. -->
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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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[More Information Needed]
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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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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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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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[More Information Needed]
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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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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- quant_method: bitsandbytes
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- load_in_8bit: True
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- load_in_4bit: False
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: fp4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float32
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### Framework versions
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- PEFT 0.6.0.dev0
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checkpoint-500/adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "/kaggle/input/vietcuna-for-binary-classification/kalapa-vietcuna-3b",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"lora_alpha": 32,
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"lora_dropout": 0.1,
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 8,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"query_key_value"
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],
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"task_type": "SEQ_CLS"
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}
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checkpoint-500/adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:bc84f9ee33f5890636c001059ed8024eba9f7b951b63ab62fd2202c9d1e25ffb
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size 9873829
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checkpoint-500/optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:2b56684755656fa2ff1211b7c22bf6db2a30451389b81f4be25ec647702d5028
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size 42788
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checkpoint-500/rng_state.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:75f760f829b44edae2a2be950380f961c72b52b6d2def775e5da9330c9837056
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size 14244
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checkpoint-500/scheduler.pt
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:4b9105f9ddc416de984dcfbba85753bcd17de130f398fcf8c52b40a5816c0c95
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size 1064
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checkpoint-500/special_tokens_map.json
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{
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"bos_token": "<s>",
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"eos_token": "</s>",
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"pad_token": "<pad>",
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"sep_token": "[SEP]",
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"unk_token": "<unk>"
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}
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checkpoint-500/tokenizer.json
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:17a208233d2ee8d8c83b23bc214df737c44806a1919f444e89b31e586cd956ba
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size 14500471
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checkpoint-500/tokenizer_config.json
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{
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"add_prefix_space": false,
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"added_tokens_decoder": {
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"0": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"2": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"3": {
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"content": "<pad>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
|
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"bos_token": "<s>",
|
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"clean_up_tokenization_spaces": false,
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"eos_token": "</s>",
|
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<pad>",
|
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"sep_token": "[SEP]",
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"tokenizer_class": "BloomTokenizer",
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"unk_token": "<unk>"
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}
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checkpoint-500/trainer_state.json
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