End of training
Browse files- README.md +38 -180
- config.json +89 -0
- generation_config.json +6 -0
- model.safetensors +3 -0
- training_args.bin +3 -0
README.md
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- **Funded by [optional]:** [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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<!-- 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 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 Dataset 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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[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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### 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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## Technical Specifications [optional]
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### Model Architecture and Objective
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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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**APA:**
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## Glossary [optional]
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## More Information [optional]
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## Model Card Authors [optional]
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## Model Card Contact
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license: other
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base_model: apple/OpenELM-270M
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tags:
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- trl
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- orpo
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- generated_from_trainer
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model-index:
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- name: ft-openelm-270m-ultrafeedback
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results: []
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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-openelm-270m-ultrafeedback
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This model is a fine-tuned version of [apple/OpenELM-270M](https://huggingface.co/apple/OpenELM-270M) on the HuggingFaceH4/ultrafeedback_binarized dataset.
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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: 8e-06
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1
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### Training results
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.1.2
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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config.json
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{
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"_name_or_path": "apple/OpenELM-270M",
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"activation_fn_name": "swish",
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"architectures": [
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"OpenELMForCausalLM"
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],
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"auto_map": {
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"AutoConfig": "apple/OpenELM-270M--configuration_openelm.OpenELMConfig",
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"AutoModelForCausalLM": "apple/OpenELM-270M--modeling_openelm.OpenELMForCausalLM"
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},
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"bos_token_id": 1,
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"eos_token_id": 2,
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"ffn_dim_divisor": 256,
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"ffn_multipliers": [
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0.5,
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0.73,
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0.97,
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1.2,
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1.43,
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1.67,
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1.9,
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2.13,
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2.37,
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2.6,
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2.83,
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3.07,
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3.3,
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3.53,
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3.77,
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4.0
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],
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"ffn_with_glu": true,
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"head_dim": 64,
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"initializer_range": 0.02,
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"max_context_length": 2048,
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"model_dim": 1280,
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"model_type": "openelm",
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"normalization_layer_name": "rms_norm",
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"normalize_qk_projections": true,
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"num_gqa_groups": 4,
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"num_kv_heads": [
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3,
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],
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"num_query_heads": [
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12,
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12,
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12,
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],
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"num_transformer_layers": 16,
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"qkv_multipliers": [
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0.5,
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1.0
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],
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"rope_freq_constant": 10000,
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"rope_max_length": 4096,
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"share_input_output_layers": true,
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"torch_dtype": "float16",
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"transformers_version": "4.39.3",
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"use_cache": true,
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"vocab_size": 32000
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"transformers_version": "4.39.3"
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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:f8cf2320132870871e63e21ceb620887a6b8d5033bf804a5e20cbcf75ef23eaf
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size 543068816
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:6f0defbfdf61a624064796d97dd1faeef3d3578d0aff1e5f0368ba4f386c9a49
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size 5240
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